{"about":{"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.","site":"https://codewithpapers.app","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","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/weakly-supervised-semantic-segmentation-1/papers/3","list_of":"/task/weakly-supervised-semantic-segmentation-1","task":"Weakly supervised Semantic Segmentation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":3,"rows_per_page":100,"rows":[201,284],"of":284,"counts":{"archive_papers_tagged":284,"with_a_code_link":160,"where_syntology_ran_a_sample":37,"not_listed_spam_title":0,"listed":284,"listed_where_code_ran":37,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":32,"every_run_a_failure_of_syntologys_instrument":5,"listed_with_a_run_with_no_instrument_failure":32,"listed_every_run_a_failure_of_syntologys_instrument":5,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/weakly-supervised-semantic-segmentation-1","prev":"/task/weakly-supervised-semantic-segmentation-1/papers/2","next":null,"papers":[{"url":null,"slug":"weakly-supervised-semantic-segmentation-of-4","title":"Weakly-Supervised Semantic Segmentation of Ships Using Thermal Imagery","date":"2022-12-26","arxiv_id":"2212.13170","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-candidate-rectification-for-weakly","title":"Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation","date":"2022-11-22","arxiv_id":"2211.12268","repositories_listed":0,"syntology":null},{"url":null,"slug":"attention-based-class-activation-diffusion","title":"Attention-based Class Activation Diffusion for Weakly-Supervised Semantic Segmentation","date":"2022-11-20","arxiv_id":"2211.10931","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-of-6","title":"Weakly Supervised Semantic Segmentation of Echocardiography Videos via Multi-level Features Selection","date":"2022-10-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"slam-semantic-learning-based-activation-map","title":"SLAMs: Semantic Learning based Activation Map for Weakly Supervised Semantic Segmentation","date":"2022-10-22","arxiv_id":"2210.12417","repositories_listed":0,"syntology":null},{"url":null,"slug":"hypergraph-convolutional-networks-for-weakly","title":"Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation","date":"2022-10-11","arxiv_id":"2210.05564","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-shape-cues-for-weakly-supervised","title":"Exploiting Shape Cues for Weakly Supervised Semantic Segmentation","date":"2022-08-08","arxiv_id":"2208.04286","repositories_listed":0,"syntology":null},{"url":null,"slug":"lapseg3d-weakly-supervised-semantic","title":"LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes","date":"2022-07-15","arxiv_id":"2207.07418","repositories_listed":0,"syntology":null},{"url":null,"slug":"ex-vit-a-novel-explainable-vision-transformer","title":"eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation","date":"2022-07-12","arxiv_id":"2207.05358","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixed-unet-refined-class-activation-mapping","title":"Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference","date":"2022-05-06","arxiv_id":"2205.04227","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-weird-trick-to-improve-your-semi-weakly","title":"One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model","date":"2022-05-02","arxiv_id":"2205.01233","repositories_listed":0,"syntology":null},{"url":null,"slug":"wsss4luad-grand-challenge-on-weakly","title":"WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma","date":"2022-04-13","arxiv_id":"2204.06455","repositories_listed":0,"syntology":null},{"url":null,"slug":"anti-adversarially-manipulated-attributions-1","title":"Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization","date":"2022-04-11","arxiv_id":"2204.04890","repositories_listed":0,"syntology":null},{"url":null,"slug":"wegformer-transformers-for-weakly-supervised","title":"WegFormer: Transformers for Weakly Supervised Semantic Segmentation","date":"2022-03-16","arxiv_id":"2203.08421","repositories_listed":0,"syntology":null},{"url":null,"slug":"pointmatch-a-consistency-training-framework","title":"PointMatch: A Consistency Training Framework for Weakly Supervised Semantic Segmentation of 3D Point Clouds","date":"2022-02-22","arxiv_id":"2202.10705","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-of-3","title":"Weakly Supervised Semantic Segmentation of Remote Sensing Images for Tree Species Classification Based on Explanation Methods","date":"2022-01-19","arxiv_id":"2201.07495","repositories_listed":0,"syntology":null},{"url":null,"slug":"muscle-a-multi-strategy-contrastive-learning","title":"MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation","date":"2022-01-18","arxiv_id":"2201.07021","repositories_listed":0,"syntology":null},{"url":null,"slug":"c-cam-causal-cam-for-weakly-supervised","title":"C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical Image","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"clims-cross-language-image-matching-for","title":"CLIMS: Cross Language Image Matching for Weakly Supervised Semantic Segmentation","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-noiseless-object-contours-for-weakly","title":"Towards Noiseless Object Contours for Weakly Supervised Semantic Segmentation","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-via","title":"Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching","date":"2021-12-17","arxiv_id":"2112.09459","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-pixel-level-self-supervision-for","title":"Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation","date":"2021-12-10","arxiv_id":"2112.05351","repositories_listed":0,"syntology":null},{"url":null,"slug":"ssa-semantic-structure-aware-inference-for","title":"SSA: Semantic Structure Aware Inference for Weakly Pixel-Wise Dense Predictions without Cost","date":"2021-11-05","arxiv_id":"2111.03392","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-by-1","title":"Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty","date":"2021-10-12","arxiv_id":"2110.05926","repositories_listed":0,"syntology":null},{"url":null,"slug":"maximize-the-exploration-of-congeneric","title":"Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation","date":"2021-10-08","arxiv_id":"2110.03982","repositories_listed":0,"syntology":null},{"url":null,"slug":"weak-shot-semantic-segmentation-by","title":"Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary","date":"2021-10-04","arxiv_id":"2110.01519","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-of-2","title":"Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke","date":"2021-09-04","arxiv_id":"2109.01887","repositories_listed":0,"syntology":null},{"url":null,"slug":"seminar-learning-for-click-level-weakly","title":"Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation","date":"2021-08-30","arxiv_id":"2108.13393","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-affinity-loss-and-erroneous-pseudo","title":"Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation","date":"2021-08-03","arxiv_id":"2108.01344","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-feature-regularized-loss-for-weakly","title":"Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation","date":"2021-08-03","arxiv_id":"2108.01296","repositories_listed":0,"syntology":null},{"url":null,"slug":"dense-supervision-propagation-for-weakly","title":"Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds","date":"2021-07-23","arxiv_id":"2107.11267","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecs-net-improving-weakly-supervised-semantic","title":"ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperspectral-image-semantic-segmentation-in","title":"Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image","date":"2020-12-18","arxiv_id":"2012.10122","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-guided-weakly-supervised-semantic","title":"3D Guided Weakly Supervised Semantic Segmentation","date":"2020-12-01","arxiv_id":"2012.00242","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-centroid-loss-for-weakly-supervised","title":"A Weakly-Supervised Semantic Segmentation Approach based on the Centroid Loss: Application to Quality Control and Inspection","date":"2020-10-26","arxiv_id":"2010.13433","repositories_listed":0,"syntology":null},{"url":null,"slug":"lid-2020-the-learning-from-imperfect-data","title":"LID 2020: The Learning from Imperfect Data Challenge Results","date":"2020-10-17","arxiv_id":"2010.11724","repositories_listed":0,"syntology":null},{"url":null,"slug":"zoom-cam-generating-fine-grained-pixel","title":"Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels","date":"2020-10-16","arxiv_id":"2010.08644","repositories_listed":0,"syntology":null},{"url":"/paper/causal-intervention-for-weakly-supervised","slug":"causal-intervention-for-weakly-supervised","title":"Causal Intervention for Weakly-Supervised Semantic Segmentation","date":"2020-09-26","arxiv_id":"2009.12547","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixup-cam-weakly-supervised-semantic","title":"Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization","date":"2020-08-03","arxiv_id":"2008.01201","repositories_listed":0,"syntology":null},{"url":null,"slug":"employing-multi-estimations-for-weakly","title":"Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation","date":"2020-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-semantic-segmentation-via-1","title":"Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network","date":"2020-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"splitting-vs-merging-mining-object-regions","title":"Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation","date":"2020-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pcams-weakly-supervised-semantic-segmentation","title":"PCAMs: Weakly Supervised Semantic Segmentation Using Point Supervision","date":"2020-07-10","arxiv_id":"2007.05615","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-miner-object-adaptive-region-mining-for","title":"Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation","date":"2020-06-14","arxiv_id":"2006.07834","repositories_listed":0,"syntology":null},{"url":null,"slug":"nopeopleallowed-the-three-step-approach-to","title":"NoPeopleAllowed: The Three-Step Approach to Weakly Supervised Semantic Segmentation","date":"2020-06-13","arxiv_id":"2006.07601","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-in-3d","title":"Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes","date":"2020-04-26","arxiv_id":"2004.12498","repositories_listed":0,"syntology":null},{"url":null,"slug":"realizing-pixel-level-semantic-learning-in","title":"Realizing Pixel-Level Semantic Learning in Complex Driving Scenes based on Only One Annotated Pixel per Class","date":"2020-03-10","arxiv_id":"2003.04671","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-by-2","title":"Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning","date":"2020-02-19","arxiv_id":"2002.08098","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-diffusion-distance-for-image","title":"Neural Diffusion Distance for Image Segmentation","date":"2019-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"attention-bridging-network-for-knowledge","title":"Attention Bridging Network for Knowledge Transfer","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"information-entropy-based-feature-pooling-for","title":"Information Entropy Based Feature Pooling for Convolutional Neural Networks","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-using-3","title":"Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets","date":"2019-09-20","arxiv_id":"1909.09414","repositories_listed":0,"syntology":null},{"url":null,"slug":"frame-to-frame-aggregation-of-active-regions","title":"Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation","date":"2019-08-13","arxiv_id":"1908.04501","repositories_listed":0,"syntology":null},{"url":null,"slug":"gated-crf-loss-for-weakly-supervised-semantic","title":"Gated CRF Loss for Weakly Supervised Semantic Image Segmentation","date":"2019-06-11","arxiv_id":"1906.04651","repositories_listed":0,"syntology":null},{"url":null,"slug":"movable-object-aware-visual-slam-via-weakly","title":"Movable-Object-Aware Visual SLAM via Weakly Supervised Semantic Segmentation","date":"2019-06-09","arxiv_id":"1906.03629","repositories_listed":0,"syntology":null},{"url":null,"slug":"closed-loop-adaptation-for-weakly-supervised","title":"Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation","date":"2019-05-29","arxiv_id":"1905.12190","repositories_listed":0,"syntology":null},{"url":null,"slug":"harvesting-information-from-captions-for","title":"Harvesting Information from Captions for Weakly Supervised Semantic Segmentation","date":"2019-05-16","arxiv_id":"1905.06784","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-of","title":"Weakly Supervised Semantic Segmentation of Satellite Images","date":"2019-04-08","arxiv_id":"1904.03983","repositories_listed":0,"syntology":null},{"url":null,"slug":"fully-using-classifiers-for-weakly-supervised","title":"Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues","date":"2019-04-03","arxiv_id":"1904.01749","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-effect-of-scene-context-on-weakly","title":"The effect of scene context on weakly supervised semantic segmentation","date":"2019-02-12","arxiv_id":"1902.04356","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-segmentation-masks-with-the","title":"Learning Segmentation Masks with the Independence Prior","date":"2018-11-12","arxiv_id":"1811.04682","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-self-guided-dense-annotations-for","title":"Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation","date":"2018-10-16","arxiv_id":"1810.07050","repositories_listed":0,"syntology":null},{"url":"/paper/associating-inter-image-salient-instances-for","slug":"associating-inter-image-salient-instances-for","title":"Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-closing-the-gap-in-weakly-supervised","title":"Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models","date":"2018-08-05","arxiv_id":"1808.01625","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-by","title":"Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features","date":"2018-06-12","arxiv_id":"1806.04659","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoupled-spatial-neural-attention-for-weakly","title":"Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation","date":"2018-03-07","arxiv_id":"1803.02563","repositories_listed":0,"syntology":null},{"url":"/paper/multi-evidence-filtering-and-fusion-for-multi","slug":"multi-evidence-filtering-and-fusion-for-multi","title":"Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning","date":"2018-02-26","arxiv_id":"1802.09129","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-random-walk-label-propagation-for","title":"Learning random-walk label propagation for weakly-supervised semantic segmentation","date":"2018-02-01","arxiv_id":"1802.00470","repositories_listed":0,"syntology":null},{"url":null,"slug":"bringing-background-into-the-foreground","title":"Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation","date":"2017-08-15","arxiv_id":"1708.04400","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-phase-learning-for-weakly-supervised","title":"Two-Phase Learning for Weakly Supervised Object Localization","date":"2017-08-07","arxiv_id":"1708.02108","repositories_listed":0,"syntology":null},{"url":null,"slug":"webly-supervised-semantic-segmentation","title":"Webly Supervised Semantic Segmentation","date":"2017-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-convolutional-autoencoder-approach-for","title":"A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation","date":"2017-06-15","arxiv_id":"1706.04970","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-network-built-in-priors-in","title":"Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation","date":"2017-06-06","arxiv_id":"1706.02189","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-based","title":"Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation","date":"2017-05-25","arxiv_id":"1705.09052","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-and-weakly-supervised-semantic","title":"Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network","date":"2017-03-28","arxiv_id":"1703.09695","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-region-mining-with-adversarial-erasing","title":"Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach","date":"2017-03-24","arxiv_id":"1703.08448","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-using-1","title":"Weakly Supervised Semantic Segmentation using Web-Crawled Videos","date":"2017-01-02","arxiv_id":"1701.00352","repositories_listed":0,"syntology":null},{"url":null,"slug":"bottom-up-top-down-cues-for-weakly-supervised","title":"Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation","date":"2016-12-07","arxiv_id":"1612.02101","repositories_listed":0,"syntology":null},{"url":null,"slug":"built-in-foregroundbackground-prior-for","title":"Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation","date":"2016-09-02","arxiv_id":"1609.00446","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-using","title":"Weakly-Supervised Semantic Segmentation using Motion Cues","date":"2016-03-23","arxiv_id":"1603.07188","repositories_listed":0,"syntology":null},{"url":null,"slug":"deconvolutional-feature-stacking-for-weakly","title":"Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation","date":"2016-02-16","arxiv_id":"1602.04984","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-transferrable-knowledge-for-semantic","title":"Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network","date":"2015-12-24","arxiv_id":"1512.07928","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-component-analysis","title":"Semantic Component Analysis","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-semantic-segmentation-for","title":"Weakly Supervised Semantic Segmentation for Social Images","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"891788f8dbcf01bd882b4b92a257b2064403b17f967cdac901a66e7026919f86","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}