A comprehensive list of weakly supervised semantic segmentation (WSSS) works from 2014 to 2022. Last updated at 2022/04/26.
For a more detailed introduction, please refer 【总结】弱监督语义分割论文汇总.
| when | what | title | where | arxiv | code |
|---|---|---|---|---|---|
| 2022/04 | L2G | L2G: A Simple Local-to-Global Knowledge Transfer Framework for Weakly Supervised Semantic Segmentation | CVPR 2022 | 2204.03206 | pytorch |
| 2022/03 | CCAM | Contrastive Learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation | CVPR 2022 | 2203.13505 | pytorch |
| 2022/03 | RCA | Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic Segmentation | CVPR 2022 | 2203.09653 | pytorch |
| 2022/03 | W-OoD | Weakly Supervised Semantic Segmentation using Out-of-Distribution Data | CVPR 2022 | 2203.03860 | github |
| 2022/03 | SIPE | Self-supervised Image-specific Prototype Exploration for Weakly Supervised Semantic Segmentation | CVPR 2022 | 2203.02909 | pytorch |
| 2022/03 | MCTformer | Multi-class Token Transformer for Weakly Supervised Semantic Segmentation | CVPR 2022 | 2203.02891 | github |
| 2022/03 | AFA | Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers | CVPR 2022 | 2203.02664 | pytorch |
| 2022/03 | CLIMS | Cross Language Image Matching for Weakly Supervised Semantic Segmentation | CVPR 2022 | 2203.02668 | pytorch |
| 2022/03 | ReCAM | Class Re-Activation Maps for Weakly-Supervised Semantic Segmentation | CVPR 2022 | 2203.00962 | pytorch |
| 2021/12 | ASDT | Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching | - | 2112.09459 | - |
| 2021/12 | AMR | Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation | AAAI 2022 | 2112.08996 | pytorch |
| 2021/12 | URN | Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation | AAAI 2022 | 2112.07431 | pytorch |
| 2021/12 | - | Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation | - | 2112.05351 | - |
| 2021/12 | SGWS | Weakly-Supervised Semantic Segmentation with Superpixel Guided Local and Global Consistency | PR 2022 | - | - |
| 2021/11 | CODNet | Co-attention Dictionary Network for Weakly-Supervised Semantic Segmentation | - | - | - |
| 2021/10 | InferCAM | Inferring the Class Conditional Response Map for Weakly Supervised Semantic Segmentation | - | 2110.14309 | pytorch |
| 2021/10 | SONet | Simpler Does It: Generating Semantic Labels with Objectness Guidance | BMVC 2021 | 2110.10335 | - |
| 2021/10 | - | End-to-end Boundary Exploration for Weakly-supervised Semantic Segmentation | ACM MM 2021 | - | - |
| 2021/10 | - | Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast | CVPR 2022 | 2110.07110 | - |
| 2021/10 | CGNet | Unlocking the Potential of Ordinary Classifier: Class-Specific Adversarial Erasing Framework for Weakly Supervised Semantic Segmentation | ICCV 2021 | - | pytorch |
| 2021/10 | ECS-Net | ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps | ICCV 2021 | - | - |
| 2021/10 | RIB | Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation | NIPS 2021 | 2110.06530 | pytorch |
| 2021/08 | - | Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation | ICCV 2021 | 2108.13393 | - |
| 2021/08 | PMM | Pseudo-mask Matters in Weakly-supervised Semantic Segmentation | ICCV 2021 | 2108.12995 | pytorch |
| 2021/08 | RPNet | Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation | TMM 2021 | 2108.07413 | pytorch |
| 2021/08 | CPN | Complementary Patch for Weakly Supervised Semantic Segmentation | ICCV 2021 | 2108.03852 | pytorch |
| 2021/08 | - | Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation | ACM MM 2021 | 2108.01344 | - |
| 2021/07 | AuxSegNet | Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation | ICCV 2021 | 2107.11787 | pytorch |
| 2021/06 | EDAM | Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation | CVPR 2021 | - | pytorch |
| 2021/05 | EPS | Railroad Is Not a Train: Saliency As Pseudo-Pixel Supervision for Weakly Supervised Semantic Segmentation | CVPR 2021 | 2105.08965 | pytorch |
| 2021/05 | SPML | Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning | ICLR 2021 | 2105.00957 | pytorch |
| 2021/04 | SBNet | Learning Structure-Aware Semantic Segmentation with Image-Level Supervision | IJCNN 2021 | 2104.07216 | pytorch |
| 2021/04 | 1T1C | One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation | CVPR 2021 | 2104.02246 | pytorch |
| 2021/04 | BAP NAL |
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation | CVPR 2021 | 2104.00905 | pytorch |
| 2021/03 | WSGCN | Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks | ICME 2021 | 2103.16762 | pytorch |
| 2021/03 | - | Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation | CVPR 2021 | 2103.14581 | pytorch |
| 2021/03 | BBAM | BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation | CVPR 2021 | 2103.08907 | pytorch |
| 2021/03 | AdvCAM | Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation | CVPR 2021 | 2103.08896 | pytorch |
| 2021/03 | DRS | Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation | AAAI 2021 | 2103.07246 | pytorch |
| 2021/03 | CDA | Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation | ICCV 2021 | 2103.01795 | pytorch |
| 2021/01 | Puzzle-CAM | Puzzle-CAM: Improved Localization via Matching Partial and Full Features | ICIP 2021 | 2101.11253 | pytorch |
| 2020/12 | GWSM | Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation | AAAI 2021 | 2012.05007 | pytorch |
| 2020/10 | PseudoSeg | PseudoSeg: Designing Pseudo Labels for Semantic Segmentation | ICLR 2021 | 2010.09713 | tensorflow |
| 2020/10 | MBMNet | Weakly Supervised Segmentation with Maximum Bipartite Graph Matching | ACM MM 2020 | - | - |
| 2020/09 | CONTA | Causal Intervention for Weakly-Supervised Semantic Segmentation | NIPS 2020 | 2009.12547 | pytorch |
| 2020/09 | LIID | Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation | TPAMI 2020 | - | pytorch |
| 2020/08 | - | Regularized Loss for Weakly Supervised Single Class Semantic Segmentation | ECCV 2020 | - | pytorch |
| 2020/08 | - | Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation | ECCV 2020 | - | - |
| 2020/08 | BES | Weakly Supervised Semantic Segmentation with Boundary Exploration | ECCV 2020 | - | pytorch |
| 2020/08 | ME | Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation | ECCV 2020 | - | - |
| 2020/08 | Mixup-CAM | Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization | BMVC 2020 | 2008.01201 | - |
| 2020/08 | SCE | Weakly-Supervised Semantic Segmentation via Sub-Category Exploration | CVPR 2020 | 2008.01183 | pytorch |
| 2020/07 | MCIS | Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation | ECCV 2020 | 2007.01947 | caffe |
| 2020/06 | ICD | Learning Integral Objects With Intra-Class Discriminator for Weakly-Supervised Semantic Segmentation | CVPR 2020 | - | mxnet |
| 2020/06 | Multi-Miner | Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation | - | 2006.07834 | - |
| 2020/06 | NoPeopleAllowed | NoPeopleAllowed: The Three-Step Approach to Weakly Supervised Semantic Segmentation | - | 2006.07601 | - |
| 2020/05 | SingleNet | Single-Stage Semantic Segmentation From Image Labels | CVPR 2020 | 2005.08104 | pytorch |
| 2020/04 | SEAM | Self-Supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation | CVPR 2020 | 2004.04581 | pytorch |
| 2020/04 | - | Learning Saliency-Free Model with Generic Features for Weakly-Supervised Semantic Segmentation | AAAI 2020 | - | - |
| 2020/02 | - | Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning | IJCV 2020 | 2002.08098 | - |
| 2019/11 | RRM | Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach | AAAI 2020 | 1911.08039 | pytorch |
| 2019/11 | SSDD | Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation | ICCV 2019 | 1911.01370 | pytorch |
| 2019/10 | OAA | Integral Object Mining via Online Attention Accumulation | ICCV 2019 | - | caffe pytorch |
| 2019/10 | EP | Information Entropy Based Feature Pooling for Convolutional Neural Networks | ICCV 2019 | - | - |
| 2019/10 | SGAN | Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic Segmentation | - | 1910.05475 | pytorch |
| 2019/09 | SSENet | Self-supervised Scale Equivariant Network for Weakly Supervised Semantic Segmentation | - | 1909.03714 | pytorch |
| 2019/09 | SSNet | Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation | ICCV 2019 | 1909.04161 | pytorch |
| 2019/06 | WS-JDS | Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation | CVPR 2019 | - | - |
| 2019/04 | IRNet | Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations | CVPR 2019 | 1904.05044 | pytorch |
| 2019/02 | FickleNet | FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference | CVPR 2019 | 1902.10421 | - |
| 2018/12 | - | Coarse-to-fine Semantic Segmentation from Image-level Labels | TIP 2019 | 1812.10885 | - |
| 2018/11 | CIAN | CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation | AAAI 2020 | 1811.10842 | mxnet |
| 2018/11 | PDML | Weakly Supervised Scene Parsing with Point-based Distance Metric Learning | AAAI 2019 | 1811.02233 | - |
| 2018/10 | SeeNet | Self-Erasing Network for Integral Object Attention | NIPS 2018 | 1810.09821 | caffe |
| 2018/10 | SGDN | Saliency Guided Deep Network for Weakly-Supervised Image Segmentation | PRL 2019 | 1810.08378 | - |
| 2018/09 | AISI | Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation | ECCV 2018 | - | - |
| 2018/06 | MCOF | Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features | CVPR 2018 | 1806.04659 | - |
| 2018/06 | DSRG | Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing | CVPR 2018 | - | caffe |
| 2018/06 | - | Bootstrapping the Performance of Webly Supervised Semantic Segmentation | CVPR 2018 | - | mxnet |
| 2018/05 | MDC | Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation | CVPR 2018 | 1805.04574 | - |
| 2018/04 | - | Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation | TIP 2019 | 1804.04882 | caffe |
| 2018/04 | Normalized Cut Loss | Normalized Cut Loss for Weakly-Supervised CNN Segmentation | CVPR 2018 | 1804.01346 | - |
| 2018/03 | AffinityNet | Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation | CVPR 2018 | 1803.10464 | pytorch |
| 2018/03 | DSNA | Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation | TMM 2019 | 1803.02563 | - |
| 2018/02 | GAIN | Tell Me Where to Look: Guided Attention Inference Network | CVPR 2018 | 1802.10171 | - |
| 2018/02 | MEFF | Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning | CVPR 2018 | 1802.09129 | - |
| 2017/08 | TPL | Two-Phase Learning for Weakly Supervised Object Localization | ICCV 2017 | 1708.02108 | - |
| 2017/07 | WILDCAT | WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation | CVPR 2017 | - | - |
| 2017/07 | DCSP | Discovering Class-Specific Pixels for Weakly Supervised Semantic Segmentation | BMVC 2017 | 1707.05821 | tensorflow |
| 2017/07 | WebS | Webly Supervised Semantic Segmentation | CVPR 2017 | - | - |
| 2017/07 | CBTS | Combining Bottom-Up, Top-Down, and Smoothness Cues for Weakly Supervised Image Segmentation | CVPR 2017 | - | - |
| 2017/03 | AE-PSL | Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach | CVPR 2017 | 1703.08448 | - |
| 2017/02 | SPN | Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network | AAAI 2017 | - | - |
| 2017/01 | Guided Segmentation | Exploiting Saliency for Object Segmentation from Image Level Labels | CVPR 2017 | 1701.08261 | caffe |
| 2017/01 | - | Weakly Supervised Semantic Segmentation using Web-Crawled Videos | CVPR 2017 | 1701.00352 | - |
| 2016/11 | SN_B | Learning to Segment with Image-Level Annotations | PR 2016 | 1705.01262 | - |
| 2016/10 | AF-MCG | Augmented Feedback in Semantic Segmentation under Image Level Supervision | ECCV 2016 | - | - |
| 2016/10 | DCSM | Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation | ECCV 2016 | - | caffe |
| 2016/09 | BFBP | Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation | ECCV 2016 | 1609.00446 | - |
| 2016/03 | SEC | Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation | ECCV 2016 | 1603.06098 | caffe pytorch |
| 2015/09 | STC | STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation | TPAMI 2017 | 1509.03150 | - |
| 2014/11 | MIL-seg | From Image-level to Pixel-level Labeling with Convolutional Networks | CVPR 2015 | 1411.6228 | tensorflow |
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