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  1. name: "ResNet-18"
  2.  
  3. layer {
  4. name: "data"
  5. type: "Input"
  6. top: "data"
  7. input_param {
  8. shape {
  9. dim: 1
  10. dim: 1
  11. dim: 720
  12. dim: 720
  13. }
  14. }
  15. }
  16.  
  17. ############## Light-ResNet Input Frames ###############
  18. layer {
  19. name: "conv1"
  20. type: "Convolution"
  21. bottom: "data"
  22. top: "conv1"
  23. convolution_param {
  24. num_output: 64
  25. pad: 3
  26. kernel_size: 7
  27. stride: 2
  28. weight_filler {
  29. type: "xavier"
  30. }
  31. bias_filler {
  32. type: "constant"
  33. value: 0.2
  34. }
  35. }
  36. }
  37. layer {
  38. name: "bn_conv1"
  39. type: "BatchNorm"
  40. bottom: "conv1"
  41. top: "conv1"
  42. batch_norm_param {
  43. }
  44. }
  45. layer {
  46. name: "scale_conv1"
  47. type: "Scale"
  48. bottom: "conv1"
  49. top: "conv1"
  50. scale_param {
  51. bias_term: true
  52. }
  53. }
  54. layer {
  55. name: "conv1_relu"
  56. type: "ReLU"
  57. bottom: "conv1"
  58. top: "conv1"
  59. }
  60. layer {
  61. name: "pool1"
  62. type: "Pooling"
  63. bottom: "conv1"
  64. top: "pool1"
  65. pooling_param {
  66. pool: MAX
  67. kernel_size: 3
  68. stride: 2
  69. }
  70. }
  71. layer {
  72. name: "res2a_branch1"
  73. type: "Convolution"
  74. bottom: "pool1"
  75. top: "res2a_branch1"
  76. convolution_param {
  77. num_output: 256
  78. bias_term: false
  79. pad: 0
  80. kernel_size: 1
  81. stride: 1
  82. weight_filler {
  83. type: "xavier"
  84. }
  85. bias_filler {
  86. type: "constant"
  87. value: 0.2
  88. }
  89. }
  90. }
  91. layer {
  92. name: "bn2a_branch1"
  93. type: "BatchNorm"
  94. bottom: "res2a_branch1"
  95. top: "res2a_branch1"
  96. batch_norm_param {
  97. }
  98. }
  99. layer {
  100. name: "scale2a_branch1"
  101. type: "Scale"
  102. bottom: "res2a_branch1"
  103. top: "res2a_branch1"
  104. scale_param {
  105. bias_term: true
  106. }
  107. }
  108. layer {
  109. name: "res2a_branch2a"
  110. type: "Convolution"
  111. bottom: "pool1"
  112. top: "res2a_branch2a"
  113. convolution_param {
  114. num_output: 64
  115. bias_term: false
  116. pad: 0
  117. kernel_size: 1
  118. stride: 1
  119. weight_filler {
  120. type: "xavier"
  121. }
  122. bias_filler {
  123. type: "constant"
  124. value: 0.2
  125. }
  126. }
  127. }
  128. layer {
  129. name: "bn2a_branch2a"
  130. type: "BatchNorm"
  131. bottom: "res2a_branch2a"
  132. top: "res2a_branch2a"
  133. batch_norm_param {
  134. }
  135. }
  136. layer {
  137. name: "scale2a_branch2a"
  138. type: "Scale"
  139. bottom: "res2a_branch2a"
  140. top: "res2a_branch2a"
  141. scale_param {
  142. bias_term: true
  143. }
  144. }
  145. layer {
  146. name: "res2a_branch2a_relu"
  147. type: "ReLU"
  148. bottom: "res2a_branch2a"
  149. top: "res2a_branch2a"
  150. }
  151. layer {
  152. name: "res2a_branch2b"
  153. type: "Convolution"
  154. bottom: "res2a_branch2a"
  155. top: "res2a_branch2b"
  156. convolution_param {
  157. num_output: 64
  158. bias_term: false
  159. pad: 1
  160. kernel_size: 3
  161. stride: 1
  162. weight_filler {
  163. type: "xavier"
  164. }
  165. bias_filler {
  166. type: "constant"
  167. value: 0.2
  168. }
  169. }
  170. }
  171. layer {
  172. name: "bn2a_branch2b"
  173. type: "BatchNorm"
  174. bottom: "res2a_branch2b"
  175. top: "res2a_branch2b"
  176. batch_norm_param {
  177. }
  178. }
  179. layer {
  180. name: "scale2a_branch2b"
  181. type: "Scale"
  182. bottom: "res2a_branch2b"
  183. top: "res2a_branch2b"
  184. scale_param {
  185. bias_term: true
  186. }
  187. }
  188. layer {
  189. name: "res2a_branch2b_relu"
  190. type: "ReLU"
  191. bottom: "res2a_branch2b"
  192. top: "res2a_branch2b"
  193. }
  194. layer {
  195. name: "res2a_branch2c"
  196. type: "Convolution"
  197. bottom: "res2a_branch2b"
  198. top: "res2a_branch2c"
  199. convolution_param {
  200. num_output: 256
  201. bias_term: false
  202. pad: 0
  203. kernel_size: 1
  204. stride: 1
  205. weight_filler {
  206. type: "xavier"
  207. }
  208. bias_filler {
  209. type: "constant"
  210. value: 0.2
  211. }
  212. }
  213. }
  214. layer {
  215. name: "bn2a_branch2c"
  216. type: "BatchNorm"
  217. bottom: "res2a_branch2c"
  218. top: "res2a_branch2c"
  219. batch_norm_param {
  220. }
  221. }
  222. layer {
  223. name: "scale2a_branch2c"
  224. type: "Scale"
  225. bottom: "res2a_branch2c"
  226. top: "res2a_branch2c"
  227. scale_param {
  228. bias_term: true
  229. }
  230. }
  231. layer {
  232. name: "res2a"
  233. type: "Eltwise"
  234. bottom: "res2a_branch1"
  235. bottom: "res2a_branch2c"
  236. top: "res2a"
  237. }
  238. layer {
  239. name: "res2a_relu"
  240. type: "ReLU"
  241. bottom: "res2a"
  242. top: "res2a"
  243. }
  244. layer {
  245. name: "res2b_branch2a"
  246. type: "Convolution"
  247. bottom: "res2a"
  248. top: "res2b_branch2a"
  249. convolution_param {
  250. num_output: 64
  251. bias_term: false
  252. pad: 0
  253. kernel_size: 1
  254. stride: 1
  255. weight_filler {
  256. type: "xavier"
  257. }
  258. bias_filler {
  259. type: "constant"
  260. value: 0.2
  261. }
  262. }
  263. }
  264. layer {
  265. name: "bn2b_branch2a"
  266. type: "BatchNorm"
  267. bottom: "res2b_branch2a"
  268. top: "res2b_branch2a"
  269. batch_norm_param {
  270. }
  271. }
  272. layer {
  273. name: "scale2b_branch2a"
  274. type: "Scale"
  275. bottom: "res2b_branch2a"
  276. top: "res2b_branch2a"
  277. scale_param {
  278. bias_term: true
  279. }
  280. }
  281. layer {
  282. name: "res2b_branch2a_relu"
  283. type: "ReLU"
  284. bottom: "res2b_branch2a"
  285. top: "res2b_branch2a"
  286. }
  287. layer {
  288. name: "res2b_branch2b"
  289. type: "Convolution"
  290. bottom: "res2b_branch2a"
  291. top: "res2b_branch2b"
  292. convolution_param {
  293. num_output: 64
  294. bias_term: false
  295. pad: 1
  296. kernel_size: 3
  297. stride: 1
  298. weight_filler {
  299. type: "xavier"
  300. }
  301. bias_filler {
  302. type: "constant"
  303. value: 0.2
  304. }
  305. }
  306. }
  307. layer {
  308. name: "bn2b_branch2b"
  309. type: "BatchNorm"
  310. bottom: "res2b_branch2b"
  311. top: "res2b_branch2b"
  312. batch_norm_param {
  313. }
  314. }
  315. layer {
  316. name: "scale2b_branch2b"
  317. type: "Scale"
  318. bottom: "res2b_branch2b"
  319. top: "res2b_branch2b"
  320. scale_param {
  321. bias_term: true
  322. }
  323. }
  324. layer {
  325. name: "res2b_branch2b_relu"
  326. type: "ReLU"
  327. bottom: "res2b_branch2b"
  328. top: "res2b_branch2b"
  329. }
  330. layer {
  331. name: "res2b_branch2c"
  332. type: "Convolution"
  333. bottom: "res2b_branch2b"
  334. top: "res2b_branch2c"
  335. convolution_param {
  336. num_output: 256
  337. bias_term: false
  338. pad: 0
  339. kernel_size: 1
  340. stride: 1
  341. weight_filler {
  342. type: "xavier"
  343. }
  344. bias_filler {
  345. type: "constant"
  346. value: 0.2
  347. }
  348. }
  349. }
  350. layer {
  351. name: "bn2b_branch2c"
  352. type: "BatchNorm"
  353. bottom: "res2b_branch2c"
  354. top: "res2b_branch2c"
  355. batch_norm_param {
  356. }
  357. }
  358. layer {
  359. name: "scale2b_branch2c"
  360. type: "Scale"
  361. bottom: "res2b_branch2c"
  362. top: "res2b_branch2c"
  363. scale_param {
  364. bias_term: true
  365. }
  366. }
  367. layer {
  368. name: "res2b"
  369. type: "Eltwise"
  370. bottom: "res2a"
  371. bottom: "res2b_branch2c"
  372. top: "res2b"
  373. }
  374. layer {
  375. name: "res2b_relu"
  376. type: "ReLU"
  377. bottom: "res2b"
  378. top: "res2b"
  379. }
  380. layer {
  381. name: "res2c_branch2a"
  382. type: "Convolution"
  383. bottom: "res2b"
  384. top: "res2c_branch2a"
  385. convolution_param {
  386. num_output: 64
  387. bias_term: false
  388. pad: 0
  389. kernel_size: 1
  390. stride: 1
  391. weight_filler {
  392. type: "xavier"
  393. }
  394. bias_filler {
  395. type: "constant"
  396. value: 0.2
  397. }
  398. }
  399. }
  400. layer {
  401. name: "bn2c_branch2a"
  402. type: "BatchNorm"
  403. bottom: "res2c_branch2a"
  404. top: "res2c_branch2a"
  405. batch_norm_param {
  406. }
  407. }
  408. layer {
  409. name: "scale2c_branch2a"
  410. type: "Scale"
  411. bottom: "res2c_branch2a"
  412. top: "res2c_branch2a"
  413. scale_param {
  414. bias_term: true
  415. }
  416. }
  417. layer {
  418. name: "res2c_branch2a_relu"
  419. type: "ReLU"
  420. bottom: "res2c_branch2a"
  421. top: "res2c_branch2a"
  422. }
  423. layer {
  424. name: "res2c_branch2b"
  425. type: "Convolution"
  426. bottom: "res2c_branch2a"
  427. top: "res2c_branch2b"
  428. convolution_param {
  429. num_output: 64
  430. bias_term: false
  431. pad: 1
  432. kernel_size: 3
  433. stride: 1
  434. weight_filler {
  435. type: "xavier"
  436. }
  437. bias_filler {
  438. type: "constant"
  439. value: 0.2
  440. }
  441. }
  442. }
  443. layer {
  444. name: "bn2c_branch2b"
  445. type: "BatchNorm"
  446. bottom: "res2c_branch2b"
  447. top: "res2c_branch2b"
  448. batch_norm_param {
  449. }
  450. }
  451. layer {
  452. name: "scale2c_branch2b"
  453. type: "Scale"
  454. bottom: "res2c_branch2b"
  455. top: "res2c_branch2b"
  456. scale_param {
  457. bias_term: true
  458. }
  459. }
  460. layer {
  461. name: "res2c_branch2b_relu"
  462. type: "ReLU"
  463. bottom: "res2c_branch2b"
  464. top: "res2c_branch2b"
  465. }
  466. layer {
  467. name: "res2c_branch2c"
  468. type: "Convolution"
  469. bottom: "res2c_branch2b"
  470. top: "res2c_branch2c"
  471. convolution_param {
  472. num_output: 256
  473. bias_term: false
  474. pad: 0
  475. kernel_size: 1
  476. stride: 1
  477. weight_filler {
  478. type: "xavier"
  479. }
  480. bias_filler {
  481. type: "constant"
  482. value: 0.2
  483. }
  484. }
  485. }
  486. layer {
  487. name: "bn2c_branch2c"
  488. type: "BatchNorm"
  489. bottom: "res2c_branch2c"
  490. top: "res2c_branch2c"
  491. batch_norm_param {
  492. }
  493. }
  494. layer {
  495. name: "scale2c_branch2c"
  496. type: "Scale"
  497. bottom: "res2c_branch2c"
  498. top: "res2c_branch2c"
  499. scale_param {
  500. bias_term: true
  501. }
  502. }
  503. layer {
  504. name: "res2c"
  505. type: "Eltwise"
  506. bottom: "res2b"
  507. bottom: "res2c_branch2c"
  508. top: "res2c"
  509. }
  510. layer {
  511. name: "res2c_relu"
  512. type: "ReLU"
  513. bottom: "res2c"
  514. top: "res2c"
  515. }
  516. layer {
  517. name: "res3a_branch1"
  518. type: "Convolution"
  519. bottom: "res2c"
  520. top: "res3a_branch1"
  521. convolution_param {
  522. num_output: 512
  523. bias_term: false
  524. pad: 0
  525. kernel_size: 1
  526. stride: 2
  527. weight_filler {
  528. type: "xavier"
  529. }
  530. bias_filler {
  531. type: "constant"
  532. value: 0.2
  533. }
  534. }
  535. }
  536. layer {
  537. name: "bn3a_branch1"
  538. type: "BatchNorm"
  539. bottom: "res3a_branch1"
  540. top: "res3a_branch1"
  541. batch_norm_param {
  542. }
  543. }
  544. layer {
  545. name: "scale3a_branch1"
  546. type: "Scale"
  547. bottom: "res3a_branch1"
  548. top: "res3a_branch1"
  549. scale_param {
  550. bias_term: true
  551. }
  552. }
  553. layer {
  554. name: "res3a_branch2a"
  555. type: "Convolution"
  556. bottom: "res2c"
  557. top: "res3a_branch2a"
  558. convolution_param {
  559. num_output: 128
  560. bias_term: false
  561. pad: 0
  562. kernel_size: 1
  563. stride: 2
  564. weight_filler {
  565. type: "xavier"
  566. }
  567. bias_filler {
  568. type: "constant"
  569. value: 0.2
  570. }
  571. }
  572. }
  573. layer {
  574. name: "bn3a_branch2a"
  575. type: "BatchNorm"
  576. bottom: "res3a_branch2a"
  577. top: "res3a_branch2a"
  578. batch_norm_param {
  579. }
  580. }
  581. layer {
  582. name: "scale3a_branch2a"
  583. type: "Scale"
  584. bottom: "res3a_branch2a"
  585. top: "res3a_branch2a"
  586. scale_param {
  587. bias_term: true
  588. }
  589. }
  590. layer {
  591. name: "res3a_branch2a_relu"
  592. type: "ReLU"
  593. bottom: "res3a_branch2a"
  594. top: "res3a_branch2a"
  595. }
  596. layer {
  597. name: "res3a_branch2b"
  598. type: "Convolution"
  599. bottom: "res3a_branch2a"
  600. top: "res3a_branch2b"
  601. convolution_param {
  602. num_output: 128
  603. bias_term: false
  604. pad: 1
  605. kernel_size: 3
  606. stride: 1
  607. weight_filler {
  608. type: "xavier"
  609. }
  610. bias_filler {
  611. type: "constant"
  612. value: 0.2
  613. }
  614. }
  615. }
  616. layer {
  617. name: "bn3a_branch2b"
  618. type: "BatchNorm"
  619. bottom: "res3a_branch2b"
  620. top: "res3a_branch2b"
  621. batch_norm_param {
  622. }
  623. }
  624. layer {
  625. name: "scale3a_branch2b"
  626. type: "Scale"
  627. bottom: "res3a_branch2b"
  628. top: "res3a_branch2b"
  629. scale_param {
  630. bias_term: true
  631. }
  632. }
  633. layer {
  634. name: "res3a_branch2b_relu"
  635. type: "ReLU"
  636. bottom: "res3a_branch2b"
  637. top: "res3a_branch2b"
  638. }
  639. layer {
  640. name: "res3a_branch2c"
  641. type: "Convolution"
  642. bottom: "res3a_branch2b"
  643. top: "res3a_branch2c"
  644. convolution_param {
  645. num_output: 512
  646. bias_term: false
  647. pad: 0
  648. kernel_size: 1
  649. stride: 1
  650. weight_filler {
  651. type: "xavier"
  652. }
  653. bias_filler {
  654. type: "constant"
  655. value: 0.2
  656. }
  657. }
  658. }
  659. layer {
  660. name: "bn3a_branch2c"
  661. type: "BatchNorm"
  662. bottom: "res3a_branch2c"
  663. top: "res3a_branch2c"
  664. batch_norm_param {
  665. }
  666. }
  667. layer {
  668. name: "scale3a_branch2c"
  669. type: "Scale"
  670. bottom: "res3a_branch2c"
  671. top: "res3a_branch2c"
  672. scale_param {
  673. bias_term: true
  674. }
  675. }
  676. layer {
  677. name: "res3a"
  678. type: "Eltwise"
  679. bottom: "res3a_branch1"
  680. bottom: "res3a_branch2c"
  681. top: "res3a"
  682. }
  683. layer {
  684. name: "res3a_relu"
  685. type: "ReLU"
  686. bottom: "res3a"
  687. top: "res3a"
  688. }
  689. layer {
  690. name: "res3b_branch2a"
  691. type: "Convolution"
  692. bottom: "res3a"
  693. top: "res3b_branch2a"
  694. convolution_param {
  695. num_output: 128
  696. bias_term: false
  697. pad: 0
  698. kernel_size: 1
  699. stride: 1
  700. weight_filler {
  701. type: "xavier"
  702. }
  703. bias_filler {
  704. type: "constant"
  705. value: 0.2
  706. }
  707. }
  708. }
  709. layer {
  710. name: "bn3b_branch2a"
  711. type: "BatchNorm"
  712. bottom: "res3b_branch2a"
  713. top: "res3b_branch2a"
  714. batch_norm_param {
  715. }
  716. }
  717. layer {
  718. name: "scale3b_branch2a"
  719. type: "Scale"
  720. bottom: "res3b_branch2a"
  721. top: "res3b_branch2a"
  722. scale_param {
  723. bias_term: true
  724. }
  725. }
  726. layer {
  727. name: "res3b_branch2a_relu"
  728. type: "ReLU"
  729. bottom: "res3b_branch2a"
  730. top: "res3b_branch2a"
  731. }
  732. layer {
  733. name: "res3b_branch2b"
  734. type: "Convolution"
  735. bottom: "res3b_branch2a"
  736. top: "res3b_branch2b"
  737. convolution_param {
  738. num_output: 128
  739. bias_term: false
  740. pad: 1
  741. kernel_size: 3
  742. stride: 1
  743. weight_filler {
  744. type: "xavier"
  745. }
  746. bias_filler {
  747. type: "constant"
  748. value: 0.2
  749. }
  750. }
  751. }
  752. layer {
  753. name: "bn3b_branch2b"
  754. type: "BatchNorm"
  755. bottom: "res3b_branch2b"
  756. top: "res3b_branch2b"
  757. batch_norm_param {
  758. }
  759. }
  760. layer {
  761. name: "scale3b_branch2b"
  762. type: "Scale"
  763. bottom: "res3b_branch2b"
  764. top: "res3b_branch2b"
  765. scale_param {
  766. bias_term: true
  767. }
  768. }
  769. layer {
  770. name: "res3b_branch2b_relu"
  771. type: "ReLU"
  772. bottom: "res3b_branch2b"
  773. top: "res3b_branch2b"
  774. }
  775. layer {
  776. name: "res3b_branch2c"
  777. type: "Convolution"
  778. bottom: "res3b_branch2b"
  779. top: "res3b_branch2c"
  780. convolution_param {
  781. num_output: 512
  782. bias_term: false
  783. pad: 0
  784. kernel_size: 1
  785. stride: 1
  786. weight_filler {
  787. type: "xavier"
  788. }
  789. bias_filler {
  790. type: "constant"
  791. value: 0.2
  792. }
  793. }
  794. }
  795. layer {
  796. name: "bn3b_branch2c"
  797. type: "BatchNorm"
  798. bottom: "res3b_branch2c"
  799. top: "res3b_branch2c"
  800. batch_norm_param {
  801. }
  802. }
  803. layer {
  804. name: "scale3b_branch2c"
  805. type: "Scale"
  806. bottom: "res3b_branch2c"
  807. top: "res3b_branch2c"
  808. scale_param {
  809. bias_term: true
  810. }
  811. }
  812. layer {
  813. name: "res3b"
  814. type: "Eltwise"
  815. bottom: "res3a"
  816. bottom: "res3b_branch2c"
  817. top: "res3b"
  818. }
  819. layer {
  820. name: "res3b_relu"
  821. type: "ReLU"
  822. bottom: "res3b"
  823. top: "res3b"
  824. }
  825.  
  826. # -------- added by S.Ko-------
  827. layer {
  828. name: "poolFM"
  829. type: "Pooling"
  830. bottom: "res3b"
  831. top: "poolFM"
  832. pooling_param {
  833. pool: AVE
  834. kernel_size: 2
  835. stride: 2
  836. }
  837. }
  838.  
  839.  
  840. layers {
  841. name: 'upsampleFM'
  842. bottom: 'poolFM'
  843. top: 'upsampleFM'
  844. type: DECONVOLUTION
  845. weight_decay: 1
  846. weight_decay: 0
  847. convolution_param {
  848. num_output: 512
  849. pad: 0
  850. kernel_size: 2
  851. stride: 2
  852. weight_filler { type: 'xavier' }
  853. }
  854. }
  855.  
  856. layers {
  857. name: 'concatFM'
  858. type: CONCAT
  859. bottom: 'res3b'
  860. bottom: 'upsampleFM'
  861. top: 'concatFM'
  862.  
  863. }
  864.  
  865.  
  866. ############## Light-ResNet Background Frames ###############
  867. layer {
  868. name: "conv1-BG"
  869. type: "Convolution"
  870. bottom: "data"
  871. top: "conv1-BG"
  872. convolution_param {
  873. num_output: 64
  874. pad: 3
  875. kernel_size: 7
  876. stride: 2
  877. weight_filler {
  878. type: "xavier"
  879. }
  880. bias_filler {
  881. type: "constant"
  882. value: 0.2
  883. }
  884. }
  885. }
  886. layer {
  887. name: "bn_conv1-BG"
  888. type: "BatchNorm"
  889. bottom: "conv1-BG"
  890. top: "conv1-BG"
  891. batch_norm_param {
  892. }
  893. }
  894. layer {
  895. name: "scale_conv1-BG"
  896. type: "Scale"
  897. bottom: "conv1-BG"
  898. top: "conv1-BG"
  899. scale_param {
  900. bias_term: true
  901. }
  902. }
  903. layer {
  904. name: "conv1_relu-BG"
  905. type: "ReLU"
  906. bottom: "conv1-BG"
  907. top: "conv1-BG"
  908. }
  909. layer {
  910. name: "pool1-BG"
  911. type: "Pooling"
  912. bottom: "conv1-BG"
  913. top: "pool1-BG"
  914. pooling_param {
  915. pool: MAX
  916. kernel_size: 3
  917. stride: 2
  918. }
  919. }
  920. layer {
  921. name: "res2a_branch1-BG"
  922. type: "Convolution"
  923. bottom: "pool1-BG"
  924. top: "res2a_branch1-BG"
  925. convolution_param {
  926. num_output: 256
  927. bias_term: false
  928. pad: 0
  929. kernel_size: 1
  930. stride: 1
  931. weight_filler {
  932. type: "xavier"
  933. }
  934. bias_filler {
  935. type: "constant"
  936. value: 0.2
  937. }
  938. }
  939. }
  940. layer {
  941. name: "bn2a_branch1-BG"
  942. type: "BatchNorm"
  943. bottom: "res2a_branch1-BG"
  944. top: "res2a_branch1-BG"
  945. batch_norm_param {
  946. }
  947. }
  948. layer {
  949. name: "scale2a_branch1-BG"
  950. type: "Scale"
  951. bottom: "res2a_branch1-BG"
  952. top: "res2a_branch1-BG"
  953. scale_param {
  954. bias_term: true
  955. }
  956. }
  957. layer {
  958. name: "res2a_branch2a-BG"
  959. type: "Convolution"
  960. bottom: "pool1-BG"
  961. top: "res2a_branch2a-BG"
  962. convolution_param {
  963. num_output: 64
  964. bias_term: false
  965. pad: 0
  966. kernel_size: 1
  967. stride: 1
  968. weight_filler {
  969. type: "xavier"
  970. }
  971. bias_filler {
  972. type: "constant"
  973. value: 0.2
  974. }
  975. }
  976. }
  977. layer {
  978. name: "bn2a_branch2a-BG"
  979. type: "BatchNorm"
  980. bottom: "res2a_branch2a-BG"
  981. top: "res2a_branch2a-BG"
  982. batch_norm_param {
  983. }
  984. }
  985. layer {
  986. name: "scale2a_branch2a-BG"
  987. type: "Scale"
  988. bottom: "res2a_branch2a-BG"
  989. top: "res2a_branch2a-BG"
  990. scale_param {
  991. bias_term: true
  992. }
  993. }
  994. layer {
  995. name: "res2a_branch2a_relu-BG"
  996. type: "ReLU"
  997. bottom: "res2a_branch2a-BG"
  998. top: "res2a_branch2a-BG"
  999. }
  1000. layer {
  1001. name: "res2a_branch2b-BG"
  1002. type: "Convolution"
  1003. bottom: "res2a_branch2a-BG"
  1004. top: "res2a_branch2b-BG"
  1005. convolution_param {
  1006. num_output: 64
  1007. bias_term: false
  1008. pad: 1
  1009. kernel_size: 3
  1010. stride: 1
  1011. weight_filler {
  1012. type: "xavier"
  1013. }
  1014. bias_filler {
  1015. type: "constant"
  1016. value: 0.2
  1017. }
  1018. }
  1019. }
  1020. layer {
  1021. name: "bn2a_branch2b-BG"
  1022. type: "BatchNorm"
  1023. bottom: "res2a_branch2b-BG"
  1024. top: "res2a_branch2b-BG"
  1025. batch_norm_param {
  1026. }
  1027. }
  1028. layer {
  1029. name: "scale2a_branch2b-BG"
  1030. type: "Scale"
  1031. bottom: "res2a_branch2b-BG"
  1032. top: "res2a_branch2b-BG"
  1033. scale_param {
  1034. bias_term: true
  1035. }
  1036. }
  1037. layer {
  1038. name: "res2a_branch2b_relu-BG"
  1039. type: "ReLU"
  1040. bottom: "res2a_branch2b-BG"
  1041. top: "res2a_branch2b-BG"
  1042. }
  1043. layer {
  1044. name: "res2a_branch2c-BG"
  1045. type: "Convolution"
  1046. bottom: "res2a_branch2b-BG"
  1047. top: "res2a_branch2c-BG"
  1048. convolution_param {
  1049. num_output: 256
  1050. bias_term: false
  1051. pad: 0
  1052. kernel_size: 1
  1053. stride: 1
  1054. weight_filler {
  1055. type: "xavier"
  1056. }
  1057. bias_filler {
  1058. type: "constant"
  1059. value: 0.2
  1060. }
  1061. }
  1062. }
  1063. layer {
  1064. name: "bn2a_branch2c-BG"
  1065. type: "BatchNorm"
  1066. bottom: "res2a_branch2c-BG"
  1067. top: "res2a_branch2c-BG"
  1068. batch_norm_param {
  1069. }
  1070. }
  1071. layer {
  1072. name: "scale2a_branch2c-BG"
  1073. type: "Scale"
  1074. bottom: "res2a_branch2c-BG"
  1075. top: "res2a_branch2c-BG"
  1076. scale_param {
  1077. bias_term: true
  1078. }
  1079. }
  1080. layer {
  1081. name: "res2a-BG"
  1082. type: "Eltwise"
  1083. bottom: "res2a_branch1-BG"
  1084. bottom: "res2a_branch2c-BG"
  1085. top: "res2a-BG"
  1086. }
  1087. layer {
  1088. name: "res2a_relu-BG"
  1089. type: "ReLU"
  1090. bottom: "res2a-BG"
  1091. top: "res2a-BG"
  1092. }
  1093. layer {
  1094. name: "res2b_branch2a-BG"
  1095. type: "Convolution"
  1096. bottom: "res2a-BG"
  1097. top: "res2b_branch2a-BG"
  1098. convolution_param {
  1099. num_output: 64
  1100. bias_term: false
  1101. pad: 0
  1102. kernel_size: 1
  1103. stride: 1
  1104. weight_filler {
  1105. type: "xavier"
  1106. }
  1107. bias_filler {
  1108. type: "constant"
  1109. value: 0.2
  1110. }
  1111. }
  1112. }
  1113. layer {
  1114. name: "bn2b_branch2a-BG"
  1115. type: "BatchNorm"
  1116. bottom: "res2b_branch2a-BG"
  1117. top: "res2b_branch2a-BG"
  1118. batch_norm_param {
  1119. }
  1120. }
  1121. layer {
  1122. name: "scale2b_branch2a-BG"
  1123. type: "Scale"
  1124. bottom: "res2b_branch2a-BG"
  1125. top: "res2b_branch2a-BG"
  1126. scale_param {
  1127. bias_term: true
  1128. }
  1129. }
  1130. layer {
  1131. name: "res2b_branch2a_relu-BG"
  1132. type: "ReLU"
  1133. bottom: "res2b_branch2a-BG"
  1134. top: "res2b_branch2a-BG"
  1135. }
  1136. layer {
  1137. name: "res2b_branch2b-BG"
  1138. type: "Convolution"
  1139. bottom: "res2b_branch2a-BG"
  1140. top: "res2b_branch2b-BG"
  1141. convolution_param {
  1142. num_output: 64
  1143. bias_term: false
  1144. pad: 1
  1145. kernel_size: 3
  1146. stride: 1
  1147. weight_filler {
  1148. type: "xavier"
  1149. }
  1150. bias_filler {
  1151. type: "constant"
  1152. value: 0.2
  1153. }
  1154. }
  1155. }
  1156. layer {
  1157. name: "bn2b_branch2b-BG"
  1158. type: "BatchNorm"
  1159. bottom: "res2b_branch2b-BG"
  1160. top: "res2b_branch2b-BG"
  1161. batch_norm_param {
  1162. }
  1163. }
  1164. layer {
  1165. name: "scale2b_branch2b-BG"
  1166. type: "Scale"
  1167. bottom: "res2b_branch2b-BG"
  1168. top: "res2b_branch2b-BG"
  1169. scale_param {
  1170. bias_term: true
  1171. }
  1172. }
  1173. layer {
  1174. name: "res2b_branch2b_relu-BG"
  1175. type: "ReLU"
  1176. bottom: "res2b_branch2b-BG"
  1177. top: "res2b_branch2b-BG"
  1178. }
  1179. layer {
  1180. name: "res2b_branch2c-BG"
  1181. type: "Convolution"
  1182. bottom: "res2b_branch2b-BG"
  1183. top: "res2b_branch2c-BG"
  1184. convolution_param {
  1185. num_output: 256
  1186. bias_term: false
  1187. pad: 0
  1188. kernel_size: 1
  1189. stride: 1
  1190. weight_filler {
  1191. type: "xavier"
  1192. }
  1193. bias_filler {
  1194. type: "constant"
  1195. value: 0.2
  1196. }
  1197. }
  1198. }
  1199. layer {
  1200. name: "bn2b_branch2c-BG"
  1201. type: "BatchNorm"
  1202. bottom: "res2b_branch2c-BG"
  1203. top: "res2b_branch2c-BG"
  1204. batch_norm_param {
  1205. }
  1206. }
  1207. layer {
  1208. name: "scale2b_branch2c-BG"
  1209. type: "Scale"
  1210. bottom: "res2b_branch2c-BG"
  1211. top: "res2b_branch2c-BG"
  1212. scale_param {
  1213. bias_term: true
  1214. }
  1215. }
  1216. layer {
  1217. name: "res2b-BG"
  1218. type: "Eltwise"
  1219. bottom: "res2a-BG"
  1220. bottom: "res2b_branch2c-BG"
  1221. top: "res2b-BG"
  1222. }
  1223. layer {
  1224. name: "res2b_relu-BG"
  1225. type: "ReLU"
  1226. bottom: "res2b-BG"
  1227. top: "res2b-BG"
  1228. }
  1229. layer {
  1230. name: "res2c_branch2a-BG"
  1231. type: "Convolution"
  1232. bottom: "res2b-BG"
  1233. top: "res2c_branch2a-BG"
  1234. convolution_param {
  1235. num_output: 64
  1236. bias_term: false
  1237. pad: 0
  1238. kernel_size: 1
  1239. stride: 1
  1240. weight_filler {
  1241. type: "xavier"
  1242. }
  1243. bias_filler {
  1244. type: "constant"
  1245. value: 0.2
  1246. }
  1247. }
  1248. }
  1249. layer {
  1250. name: "bn2c_branch2a-BG"
  1251. type: "BatchNorm"
  1252. bottom: "res2c_branch2a-BG"
  1253. top: "res2c_branch2a-BG"
  1254. batch_norm_param {
  1255. }
  1256. }
  1257. layer {
  1258. name: "scale2c_branch2a-BG"
  1259. type: "Scale"
  1260. bottom: "res2c_branch2a-BG"
  1261. top: "res2c_branch2a-BG"
  1262. scale_param {
  1263. bias_term: true
  1264. }
  1265. }
  1266. layer {
  1267. name: "res2c_branch2a_relu-BG"
  1268. type: "ReLU"
  1269. bottom: "res2c_branch2a-BG"
  1270. top: "res2c_branch2a-BG"
  1271. }
  1272. layer {
  1273. name: "res2c_branch2b-BG"
  1274. type: "Convolution"
  1275. bottom: "res2c_branch2a-BG"
  1276. top: "res2c_branch2b-BG"
  1277. convolution_param {
  1278. num_output: 64
  1279. bias_term: false
  1280. pad: 1
  1281. kernel_size: 3
  1282. stride: 1
  1283. weight_filler {
  1284. type: "xavier"
  1285. }
  1286. bias_filler {
  1287. type: "constant"
  1288. value: 0.2
  1289. }
  1290. }
  1291. }
  1292. layer {
  1293. name: "bn2c_branch2b-BG"
  1294. type: "BatchNorm"
  1295. bottom: "res2c_branch2b-BG"
  1296. top: "res2c_branch2b-BG"
  1297. batch_norm_param {
  1298. }
  1299. }
  1300. layer {
  1301. name: "scale2c_branch2b-BG"
  1302. type: "Scale"
  1303. bottom: "res2c_branch2b-BG"
  1304. top: "res2c_branch2b-BG"
  1305. scale_param {
  1306. bias_term: true
  1307. }
  1308. }
  1309. layer {
  1310. name: "res2c_branch2b_relu-BG"
  1311. type: "ReLU"
  1312. bottom: "res2c_branch2b-BG"
  1313. top: "res2c_branch2b-BG"
  1314. }
  1315. layer {
  1316. name: "res2c_branch2c-BG"
  1317. type: "Convolution"
  1318. bottom: "res2c_branch2b-BG"
  1319. top: "res2c_branch2c-BG"
  1320. convolution_param {
  1321. num_output: 256
  1322. bias_term: false
  1323. pad: 0
  1324. kernel_size: 1
  1325. stride: 1
  1326. weight_filler {
  1327. type: "xavier"
  1328. }
  1329. bias_filler {
  1330. type: "constant"
  1331. value: 0.2
  1332. }
  1333. }
  1334. }
  1335. layer {
  1336. name: "bn2c_branch2c-BG"
  1337. type: "BatchNorm"
  1338. bottom: "res2c_branch2c-BG"
  1339. top: "res2c_branch2c-BG"
  1340. batch_norm_param {
  1341. }
  1342. }
  1343. layer {
  1344. name: "scale2c_branch2c-BG"
  1345. type: "Scale"
  1346. bottom: "res2c_branch2c-BG"
  1347. top: "res2c_branch2c-BG"
  1348. scale_param {
  1349. bias_term: true
  1350. }
  1351. }
  1352. layer {
  1353. name: "res2c-BG"
  1354. type: "Eltwise"
  1355. bottom: "res2b-BG"
  1356. bottom: "res2c_branch2c-BG"
  1357. top: "res2c-BG"
  1358. }
  1359. layer {
  1360. name: "res2c_relu-BG"
  1361. type: "ReLU"
  1362. bottom: "res2c-BG"
  1363. top: "res2c-BG"
  1364. }
  1365. layer {
  1366. name: "res3a_branch1-BG"
  1367. type: "Convolution"
  1368. bottom: "res2c-BG"
  1369. top: "res3a_branch1-BG"
  1370. convolution_param {
  1371. num_output: 512
  1372. bias_term: false
  1373. pad: 0
  1374. kernel_size: 1
  1375. stride: 2
  1376. weight_filler {
  1377. type: "xavier"
  1378. }
  1379. bias_filler {
  1380. type: "constant"
  1381. value: 0.2
  1382. }
  1383. }
  1384. }
  1385. layer {
  1386. name: "bn3a_branch1-BG"
  1387. type: "BatchNorm"
  1388. bottom: "res3a_branch1-BG"
  1389. top: "res3a_branch1-BG"
  1390. batch_norm_param {
  1391. }
  1392. }
  1393. layer {
  1394. name: "scale3a_branch1-BG"
  1395. type: "Scale"
  1396. bottom: "res3a_branch1-BG"
  1397. top: "res3a_branch1-BG"
  1398. scale_param {
  1399. bias_term: true
  1400. }
  1401. }
  1402. layer {
  1403. name: "res3a_branch2a-BG"
  1404. type: "Convolution"
  1405. bottom: "res2c-BG"
  1406. top: "res3a_branch2a-BG"
  1407. convolution_param {
  1408. num_output: 128
  1409. bias_term: false
  1410. pad: 0
  1411. kernel_size: 1
  1412. stride: 2
  1413. weight_filler {
  1414. type: "xavier"
  1415. }
  1416. bias_filler {
  1417. type: "constant"
  1418. value: 0.2
  1419. }
  1420. }
  1421. }
  1422. layer {
  1423. name: "bn3a_branch2a-BG"
  1424. type: "BatchNorm"
  1425. bottom: "res3a_branch2a-BG"
  1426. top: "res3a_branch2a-BG"
  1427. batch_norm_param {
  1428. }
  1429. }
  1430. layer {
  1431. name: "scale3a_branch2a-BG"
  1432. type: "Scale"
  1433. bottom: "res3a_branch2a-BG"
  1434. top: "res3a_branch2a-BG"
  1435. scale_param {
  1436. bias_term: true
  1437. }
  1438. }
  1439. layer {
  1440. name: "res3a_branch2a_relu-BG"
  1441. type: "ReLU"
  1442. bottom: "res3a_branch2a-BG"
  1443. top: "res3a_branch2a-BG"
  1444. }
  1445. layer {
  1446. name: "res3a_branch2b-BG"
  1447. type: "Convolution"
  1448. bottom: "res3a_branch2a-BG"
  1449. top: "res3a_branch2b-BG"
  1450. convolution_param {
  1451. num_output: 128
  1452. bias_term: false
  1453. pad: 1
  1454. kernel_size: 3
  1455. stride: 1
  1456. weight_filler {
  1457. type: "xavier"
  1458. }
  1459. bias_filler {
  1460. type: "constant"
  1461. value: 0.2
  1462. }
  1463. }
  1464. }
  1465. layer {
  1466. name: "bn3a_branch2b-BG"
  1467. type: "BatchNorm"
  1468. bottom: "res3a_branch2b-BG"
  1469. top: "res3a_branch2b-BG"
  1470. batch_norm_param {
  1471. }
  1472. }
  1473. layer {
  1474. name: "scale3a_branch2b-BG"
  1475. type: "Scale"
  1476. bottom: "res3a_branch2b-BG"
  1477. top: "res3a_branch2b-BG"
  1478. scale_param {
  1479. bias_term: true
  1480. }
  1481. }
  1482. layer {
  1483. name: "res3a_branch2b_relu-BG"
  1484. type: "ReLU"
  1485. bottom: "res3a_branch2b-BG"
  1486. top: "res3a_branch2b-BG"
  1487. }
  1488. layer {
  1489. name: "res3a_branch2c-BG"
  1490. type: "Convolution"
  1491. bottom: "res3a_branch2b-BG"
  1492. top: "res3a_branch2c-BG"
  1493. convolution_param {
  1494. num_output: 512
  1495. bias_term: false
  1496. pad: 0
  1497. kernel_size: 1
  1498. stride: 1
  1499. weight_filler {
  1500. type: "xavier"
  1501. }
  1502. bias_filler {
  1503. type: "constant"
  1504. value: 0.2
  1505. }
  1506. }
  1507. }
  1508. layer {
  1509. name: "bn3a_branch2c-BG"
  1510. type: "BatchNorm"
  1511. bottom: "res3a_branch2c-BG"
  1512. top: "res3a_branch2c-BG"
  1513. batch_norm_param {
  1514. }
  1515. }
  1516. layer {
  1517. name: "scale3a_branch2c-BG"
  1518. type: "Scale"
  1519. bottom: "res3a_branch2c-BG"
  1520. top: "res3a_branch2c-BG"
  1521. scale_param {
  1522. bias_term: true
  1523. }
  1524. }
  1525. layer {
  1526. name: "res3a-BG"
  1527. type: "Eltwise"
  1528. bottom: "res3a_branch1-BG"
  1529. bottom: "res3a_branch2c-BG"
  1530. top: "res3a-BG"
  1531. }
  1532. layer {
  1533. name: "res3a_relu-BG"
  1534. type: "ReLU"
  1535. bottom: "res3a-BG"
  1536. top: "res3a-BG"
  1537. }
  1538. layer {
  1539. name: "res3b_branch2a-BG"
  1540. type: "Convolution"
  1541. bottom: "res3a-BG"
  1542. top: "res3b_branch2a-BG"
  1543. convolution_param {
  1544. num_output: 128
  1545. bias_term: false
  1546. pad: 0
  1547. kernel_size: 1
  1548. stride: 1
  1549. weight_filler {
  1550. type: "xavier"
  1551. }
  1552. bias_filler {
  1553. type: "constant"
  1554. value: 0.2
  1555. }
  1556. }
  1557. }
  1558. layer {
  1559. name: "bn3b_branch2a-BG"
  1560. type: "BatchNorm"
  1561. bottom: "res3b_branch2a-BG"
  1562. top: "res3b_branch2a-BG"
  1563. batch_norm_param {
  1564. }
  1565. }
  1566. layer {
  1567. name: "scale3b_branch2a-BG"
  1568. type: "Scale"
  1569. bottom: "res3b_branch2a-BG"
  1570. top: "res3b_branch2a-BG"
  1571. scale_param {
  1572. bias_term: true
  1573. }
  1574. }
  1575. layer {
  1576. name: "res3b_branch2a_relu-BG"
  1577. type: "ReLU"
  1578. bottom: "res3b_branch2a-BG"
  1579. top: "res3b_branch2a-BG"
  1580. }
  1581. layer {
  1582. name: "res3b_branch2b-BG"
  1583. type: "Convolution"
  1584. bottom: "res3b_branch2a-BG"
  1585. top: "res3b_branch2b-BG"
  1586. convolution_param {
  1587. num_output: 128
  1588. bias_term: false
  1589. pad: 1
  1590. kernel_size: 3
  1591. stride: 1
  1592. weight_filler {
  1593. type: "xavier"
  1594. }
  1595. bias_filler {
  1596. type: "constant"
  1597. value: 0.2
  1598. }
  1599. }
  1600. }
  1601. layer {
  1602. name: "bn3b_branch2b-BG"
  1603. type: "BatchNorm"
  1604. bottom: "res3b_branch2b-BG"
  1605. top: "res3b_branch2b-BG"
  1606. batch_norm_param {
  1607. }
  1608. }
  1609. layer {
  1610. name: "scale3b_branch2b-BG"
  1611. type: "Scale"
  1612. bottom: "res3b_branch2b-BG"
  1613. top: "res3b_branch2b-BG"
  1614. scale_param {
  1615. bias_term: true
  1616. }
  1617. }
  1618. layer {
  1619. name: "res3b_branch2b_relu-BG"
  1620. type: "ReLU"
  1621. bottom: "res3b_branch2b-BG"
  1622. top: "res3b_branch2b-BG"
  1623. }
  1624. layer {
  1625. name: "res3b_branch2c-BG"
  1626. type: "Convolution"
  1627. bottom: "res3b_branch2b-BG"
  1628. top: "res3b_branch2c-BG"
  1629. convolution_param {
  1630. num_output: 512
  1631. bias_term: false
  1632. pad: 0
  1633. kernel_size: 1
  1634. stride: 1
  1635. weight_filler {
  1636. type: "xavier"
  1637. }
  1638. bias_filler {
  1639. type: "constant"
  1640. value: 0.2
  1641. }
  1642. }
  1643. }
  1644. layer {
  1645. name: "bn3b_branch2c-BG"
  1646. type: "BatchNorm"
  1647. bottom: "res3b_branch2c-BG"
  1648. top: "res3b_branch2c-BG"
  1649. batch_norm_param {
  1650. }
  1651. }
  1652. layer {
  1653. name: "scale3b_branch2c-BG"
  1654. type: "Scale"
  1655. bottom: "res3b_branch2c-BG"
  1656. top: "res3b_branch2c-BG"
  1657. scale_param {
  1658. bias_term: true
  1659. }
  1660. }
  1661. layer {
  1662. name: "res3b-BG"
  1663. type: "Eltwise"
  1664. bottom: "res3a-BG"
  1665. bottom: "res3b_branch2c-BG"
  1666. top: "res3b-BG"
  1667. }
  1668. layer {
  1669. name: "res3b_relu-BG"
  1670. type: "ReLU"
  1671. bottom: "res3b-BG"
  1672. top: "res3b-BG"
  1673. }
  1674.  
  1675. # -------- added by S.Ko-------
  1676. layer {
  1677. name: "poolFM-BG"
  1678. type: "Pooling"
  1679. bottom: "res3b-BG"
  1680. top: "poolFM-BG"
  1681. pooling_param {
  1682. pool: AVE
  1683. kernel_size: 2
  1684. stride: 2
  1685. }
  1686. }
  1687.  
  1688.  
  1689. layers {
  1690. name: 'upsampleFM-BG'
  1691. bottom: 'poolFM-BG'
  1692. top: 'upsampleFM-BG'
  1693. type: DECONVOLUTION
  1694. weight_decay: 1
  1695. weight_decay: 0
  1696. convolution_param {
  1697. num_output: 512
  1698. pad: 0
  1699. kernel_size: 2
  1700. stride: 2
  1701. weight_filler { type: 'xavier' }
  1702. }
  1703. }
  1704.  
  1705. layers {
  1706. name: 'concatFM-BG'
  1707. type: CONCAT
  1708. bottom: 'res3b-BG'
  1709. bottom: 'upsampleFM-BG'
  1710. top: 'concatFM-BG'
  1711.  
  1712. }
  1713.  
  1714.  
  1715. ############## concate ###############
  1716. layers {
  1717. name: 'concatFM-SUM'
  1718. type: CONCAT
  1719. bottom: 'concatFM'
  1720. bottom: 'concatFM-BG'
  1721. top: 'concatFM-SUM'
  1722. }
  1723.  
  1724. layers { bottom: 'concatFM-SUM' top: 'd2c' name: 'conv_d2bc' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 256 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1725. layers { bottom: 'd2c' top: 'd2c' name: 'relu_d2c' type: RELU }
  1726. layers { bottom: 'd2c' top: 'd3a' name: 'pool_d2c-3a' type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
  1727. layers { bottom: 'd3a' top: 'd3b' name: 'conv_d3ab' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 512 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1728. layers { bottom: 'd3b' top: 'd3b' name: 'relu_d3b' type: RELU }
  1729. layers { bottom: 'd3b' top: 'd3c' name: 'conv_d3bc' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 512 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1730. layers { bottom: 'd3c' top: 'd3c' name: 'relu_d3c' type: RELU }
  1731. layers { bottom: 'd3c' top: 'd3c' name: 'dropout_d3c' type: DROPOUT dropout_param { dropout_ratio: 0.5 }
  1732. include: { phase: TRAIN }}
  1733. layers { bottom: 'd3c' top: 'd4a' name: 'pool_d3c-4a' type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
  1734. layers { bottom: 'd4a' top: 'd4b' name: 'conv_d4ab' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 1024 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1735. layers { bottom: 'd4b' top: 'd4b' name: 'relu_d4b' type: RELU }
  1736. layers { bottom: 'd4b' top: 'd4c' name: 'conv_d4bc' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 1024 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1737. layers { bottom: 'd4c' top: 'd4c' name: 'relu_d4c' type: RELU }
  1738. layers { bottom: 'd4c' top: 'd4c' name: 'dropout_d4c' type: DROPOUT dropout_param { dropout_ratio: 0.5 }
  1739. include: { phase: TRAIN }}
  1740. layers { bottom: 'd4c' top: 'u3a' name: 'upconv_d4c_u3a' type: DECONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 512 pad: 0 kernel_size: 2 stride: 2 weight_filler { type: 'xavier' }} }
  1741. layers { bottom: 'u3a' top: 'u3a' name: 'relu_u3a' type: RELU }
  1742. layers { bottom: 'd3c' bottom: 'u3a' top: 'd3cc' name: 'crop_d3cd3cc' type: CROP }
  1743. layers { bottom: 'u3a' bottom: 'd3cc' top: 'u3b' name: 'concat_d3cc_u3a-b' type: CONCAT }
  1744. layers { bottom: 'u3b' top: 'u3c' name: 'conv_u3bc' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 512 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1745. layers { bottom: 'u3c' top: 'u3c' name: 'relu_u3c' type: RELU }
  1746. layers { bottom: 'u3c' top: 'u3d' name: 'conv_u3cd' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 512 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
  1747. layers { bottom: 'u3d' top: 'u3d' name: 'relu_u3d' type: RELU }
  1748. layers { bottom: 'u3d' top: 'u2a' name: 'upconv_u3d_u2a' type: DECONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 256 pad: 0 kernel_size: 2 stride: 2 weight_filler { type: 'xavier' }} }
  1749. layers { bottom: 'u2a' top: 'u2a' name: 'relu_u2a' type: RELU }
  1750. layers { bottom: 'd2c' bottom: 'u2a' top: 'd2cc' name: 'crop_d2cd2cc' type: CROP }
  1751. layers { bottom: 'u2a' bottom: 'd2cc' top: 'u2b' name: 'concat_d2cc_u2a-b' type: CONCAT }
  1752. layers { bottom: 'u2b' top: 'FINAL' name: 'conv_u2bc' type: CONVOLUTION blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 256 pad: 0 kernel_size: 3 engine: CAFFE weight_filler { type: 'xavier' }} }
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