{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fully-convolutional-networks-for-semantic-1","title":"Fully Convolutional Networks for Semantic Segmentation","arxiv_id":"1411.4038","date":"2014-11-14","proceeding":"CVPR 2015 6","authors":["Jonathan Long","Evan Shelhamer","Trevor Darrell"],"abstract":"Convolutional networks are powerful visual models that yield hierarchies of\nfeatures. We show that convolutional networks by themselves, trained\nend-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic\nsegmentation. Our key insight is to build \"fully convolutional\" networks that\ntake input of arbitrary size and produce correspondingly-sized output with\nefficient inference and learning. We define and detail the space of fully\nconvolutional networks, explain their application to spatially dense prediction\ntasks, and draw connections to prior models. We adapt contemporary\nclassification networks (AlexNet, the VGG net, and GoogLeNet) into fully\nconvolutional networks and transfer their learned representations by\nfine-tuning to the segmentation task. We then define a novel architecture that\ncombines semantic information from a deep, coarse layer with appearance\ninformation from a shallow, fine layer to produce accurate and detailed\nsegmentations. Our fully convolutional network achieves state-of-the-art\nsegmentation of PASCAL VOC (20% relative improvement to 62.2% mean IU on 2012),\nNYUDv2, and SIFT Flow, while inference takes one third of a second for a\ntypical image.","url_abs":"http://arxiv.org/abs/1411.4038v2","url_pdf":"http://arxiv.org/pdf/1411.4038v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/Anirudh0707/Roads-and-Building-Segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/DLWK/EANet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/GodPater/model_fcn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/LeeMax117/FCN_8s","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/LeeMax117/week10_homework","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/Niloy-Chakraborty/Image_Segmentation_Model","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/RogerQi/pascal-5i","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/SDMrFeng/quiz-w10-fcn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/Segmentation-Road-Detection/Semantic-Segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/SethEBaldwin/FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/SophiaYuSophiaYu/FCN_SemanticSegmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/TianchengQ/FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/YigeunLee/fcn32","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/alvinwen428/featurecp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/andyzeng/apc-vision-toolbox","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"BSD-2-Clause"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/anoushkrit/Knowledge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/azraelzhor/tf-FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/colorfulxd/WK10_FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/demul/image_segmentation_project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/faroukmokhtar/ImageSegmentationPASCAL","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/frank-roesler/Image_Segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/fxfviolet/FCN_for_segmantic_segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/giovanniguidi/FCN-keras","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/githubfa/FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/guilhermesantos/Semantic-Image-Segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/hahahappyboy/GANForCartoon","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"GPL-2.0"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/hitukensinn/quiz-w9-code","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/hz-ants/apc-vision-toolbox","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"BSD-2-Clause"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/inder9999/ISIC2017_skin_lesion_segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/jqueguiner/camembert-as-a-service","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/jqueguiner/image-segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/kbardool/mrcnn3","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/koryako/AI-application","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/krutikabapat/Sematic_Segmentation_Using_Pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/lanthlove/segmentation-fcn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/martinkersner/py_img_seg_eval","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/minoring/fcn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/muramasa8191/DeepLearning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/pessimiss/ai100-w9-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/pochih/fcn-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/robromijnders/segm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/shenshutao/image_segmentation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/sigtot/unet-auto","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/stoensin/w10-cnn-SegmentationClass","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/sunnynevarekar/FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/tsixta/jnet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/zhuyi55/week10","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/Jackey9797/FCN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":{"status":"ok"}},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/MindSpore-paper-code-3/code3/tree/main/FCN8s","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"fully-convolutional-networks-for-semantic-1","repo_url":"https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"crack-segmentation","task_name":"Crack Segmentation"},{"task_slug":"multi-tissue-nucleus-segmentation","task_name":"Multi-tissue Nucleus Segmentation"},{"task_slug":"multispectral-object-detection","task_name":"Multispectral Object Detection"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"thermal-image-segmentation","task_name":"Thermal Image Segmentation"}],"methods":[{"method_slug":"average-pooling","method_name":"Average Pooling"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"global-average-pooling","method_name":"Global Average Pooling"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/crack-segmentation-on-crackvision12k","task":"Crack Segmentation","dataset":"CrackVision12K","model":"FCN","rank_in_archive_order":3,"of":4,"metrics":{"mIoU":"0.59842"},"uses_additional_data":false},{"leaderboard":"/sota/multi-tissue-nucleus-segmentation-on-kumar","task":"Multi-tissue Nucleus Segmentation","dataset":"Kumar","model":"FCN8 (e)","rank_in_archive_order":14,"of":18,"metrics":{"Dice":"0.797","Hausdorff Distance (mm)":"31.2"},"uses_additional_data":false},{"leaderboard":"/sota/multispectral-object-detection-on-kaist","task":"Multispectral Object Detection","dataset":"KAIST Multispectral Pedestrian Detection Benchmark","model":"FusionRPN+BF","rank_in_archive_order":15,"of":17,"metrics":{"All Miss Rate":"51.70"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-ade20k","task":"Semantic Segmentation","dataset":"ADE20K","model":"FCN","rank_in_archive_order":229,"of":235,"metrics":{"Validation mIoU":"29.39"},"uses_additional_data":true},{"leaderboard":"/sota/semantic-segmentation-on-coco-stuff-test","task":"Semantic Segmentation","dataset":"COCO-Stuff test","model":"FCN (VGG-16)","rank_in_archive_order":21,"of":21,"metrics":{"mIoU":"22.7%"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-event-based","task":"Semantic Segmentation","dataset":"Event-based Segmentation Dataset","model":"FCN","rank_in_archive_order":6,"of":6,"metrics":{"mIoU":"59.6"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-fine-grained-grass","task":"Semantic Segmentation","dataset":"Fine-Grained Grass Segmentation Dataset","model":"FCN","rank_in_archive_order":9,"of":10,"metrics":{"mIoU":"47.47"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-pascal-context","task":"Semantic Segmentation","dataset":"PASCAL Context","model":"FCN-8s","rank_in_archive_order":63,"of":66,"metrics":{"mIoU":"37.8"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-pascal-voc-2012","task":"Semantic Segmentation","dataset":"PASCAL VOC 2012 test","model":"FCN (VGG-16)","rank_in_archive_order":49,"of":51,"metrics":{"Mean IoU":"62.2%"},"uses_additional_data":true},{"leaderboard":"/sota/semantic-segmentation-on-selma","task":"Semantic Segmentation","dataset":"SELMA","model":"FCN","rank_in_archive_order":6,"of":7,"metrics":{"mIoU":"68.2"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-skyscapes-dense-1","task":"Semantic Segmentation","dataset":"SkyScapes-Dense","model":"FCN8s (ResNet-50)","rank_in_archive_order":3,"of":7,"metrics":{"Mean IoU":"33.06"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-skyscapes-lane-1","task":"Semantic Segmentation","dataset":"SkyScapes-Lane","model":"FCN8s (ResNet-50)","rank_in_archive_order":2,"of":2,"metrics":{"Mean IoU":"13.74"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-trans10k","task":"Semantic Segmentation","dataset":"Trans10K","model":"FCN","rank_in_archive_order":11,"of":15,"metrics":{"GFLOPs":"42.23","mIoU":"62.75%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1411.4038","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1411.4038"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/muramasa8191/DeepLearning","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/giovanniguidi/FCN-keras","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/shenshutao/image_segmentation","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/kbardool/mrcnn3","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/pessimiss/ai100-w9-master","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Jackey9797/FCN","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Anirudh0707/Roads-and-Building-Segmentation","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/sigtot/unet-auto","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceNet","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/andyzeng/apc-vision-toolbox","reach":{"status":"ok","spdx":"BSD-2-Clause"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jqueguiner/image-segmentation","reach":{"status":"ok","spdx":"GPL-3.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/TianchengQ/FCN","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/YigeunLee/fcn32","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/fxfviolet/FCN_for_segmantic_segmentation","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zhuyi55/week10","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/DLWK/EANet","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/anoushkrit/Knowledge","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/githubfa/FCN","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/stoensin/w10-cnn-SegmentationClass","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/tsixta/jnet","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/guilhermesantos/Semantic-Image-Segmentation","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/SDMrFeng/quiz-w10-fcn","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/minoring/fcn","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/hitukensinn/quiz-w9-code","reach":{"status":"ok"}}],"summary":{"ran_fixture":1,"ran_draft_wrong":2,"unverified":1},"by_repo_kind":{"listed":{"samples":4,"ran":3,"repositories":3}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":4,"samples":[{"code_sha256_prefix":"f3ca1f3716d95661","entry":"image2label","repo":"githubfa/FCN","repo_kind":"listed","path":"convert_fcn_dataset.py","file_url":"https://github.com/githubfa/FCN/blob/HEAD/convert_fcn_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f3ca1f3716d95661"}},{"code_sha256_prefix":"35e373ea432491af","entry":"make_layers","repo":"pochih/fcn-pytorch","repo_kind":"listed","path":"python/fcn.py","file_url":"https://github.com/pochih/fcn-pytorch/blob/HEAD/python/fcn.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"35e373ea432491af"}},{"code_sha256_prefix":"016fff2e8cba6727","entry":"read_images_names","repo":"githubfa/FCN","repo_kind":"listed","path":"convert_fcn_dataset.py","file_url":"https://github.com/githubfa/FCN/blob/HEAD/convert_fcn_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"016fff2e8cba6727"}},{"code_sha256_prefix":"73d1eec357fb97af","entry":"get_result","repo":"YigeunLee/fcn32","repo_kind":"listed","path":"fully_cnn.py","file_url":"https://github.com/YigeunLee/fcn32/blob/HEAD/fully_cnn.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"73d1eec357fb97af"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}