Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/YimingCuiCuiCui/awesome-weakly-supervised-segmentation


https://github.com/YimingCuiCuiCui/awesome-weakly-supervised-segmentation

List: awesome-weakly-supervised-segmentation

Last synced: about 2 months ago
JSON representation

Awesome Lists containing this project

README 

        
# Awesome-Weakly-Supervised-Segmentation[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)



 



```diff

- Recent papers (from 2015)

```






 Keywords 



__`img.`__: image level label   |   __`vid.`__: video level label   |   __`box.`__: bounding box label   |   __`ins.`__: instance segmentation    |   __`pan.`__: panotic segmentation   |    __`point.`__: point cloud segmentation



Statistics: :fire: code is available & stars >= 100  |  :star: popular & cited in a survey  | 

:sunflower: natural scene images  |  :earth_americas: remote sensing images  |  :hospital: medical images 



---

## 2020

- [[NeurIPS](https://arxiv.org/abs/2009.12547)] Causal Intervention for Weakly-Supervised Semantic Segmentation. [[pytorch](https://github.com/ZHANGDONG-NJUST/CONTA)] [__`img.`__] :sunflower:

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Wei_Multi-Path_Region_Mining_for_Weakly_Supervised_3D_Semantic_Segmentation_on_CVPR_2020_paper.html)] Multi-Path Region Mining for Weakly Supervised 3D Semantic Segmentation on Point Clouds. [[tensorflow](https://github.com/plusmultiply/mprm)] [__`point.`__] 

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Xu_Weakly_Supervised_Semantic_Point_Cloud_Segmentation_Towards_10x_Fewer_Labels_CVPR_2020_paper.html)] Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels. [[tensorflow](https://github.com/alex-xun-xu/WeakSupPointCloudSeg)] [__`point.`__] 

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Fan_Learning_Integral_Objects_With_Intra-Class_Discriminator_for_Weakly-Supervised_Semantic_Segmentation_CVPR_2020_paper.html)] Learning Integral Objects with Intra-Class Discriminator for Weakly-Supervised Semantic Segmentation. [[mxnet](https://github.com/js-fan/ICD)] [__`img.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/2005.08104v1)] Single-Stage Semantic Segmentation from Image Labels. [[pytorch](https://github.com/visinf/1-stage-wseg)] [__`img.`__] :sunflower:

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Learning_a_Weakly-Supervised_Video_Actor-Action_Segmentation_Model_With_a_Wise_CVPR_2020_paper.pdf)] Learning a Weakly-Supervised Video Actor-Action Segmentation Model with a Wise Selection [__`img.`__] :sunflower:

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Chang_Weakly-Supervised_Semantic_Segmentation_via_Sub-Category_Exploration_CVPR_2020_paper.html)] Weakly-Supervised Semantic Segmentation via Sub-Category Exploration. [[pytorch](https://github.com/Juliachang/SC-CAM)] [__`img.`__] :sunflower:

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2020/html/Wang_Self-Supervised_Equivariant_Attention_Mechanism_for_Weakly_Supervised_Semantic_Segmentation_CVPR_2020_paper.html)] Self-supervised Equivariant Attention Mechanism

for Weakly Supervised Semantic Segmentation. [[pytorch](https://github.com/YudeWang/SEAM)] [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740341.pdf)] Regularized Loss for Weakly Supervised Single Class Semantic Segmentation. [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123710341.pdf)]  Weakly Supervised Semantic Segmentation with Boundary Exploration. [__`box.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720290.pdf)] Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation. [__`box.`__] :sunflower:

- [[ECCV](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123670664.pdf)] Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123620324.pdf)] Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123600426.pdf)] Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology. [__`img.`__] :hospital:

- [[ECCV](https://arxiv.org/abs/2007.09397)] Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances. [__`img.`__,__`ins.`__] :sunflower:

- [[ECCV](https://arxiv.org/abs/2007.01947)] Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation. [[Caffe](https://github.com/GuoleiSun/MCIS_wsss)][__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123540545.pdf)] Domain Adaptive Semantic Segmentation Using Weak Labels. [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720290.pdf)]  Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation. [__`img.`__] :sunflower:

- [[ECCV](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500766.pdf)]  Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network. [__`img.`__] :sunflower:

- [[ICLR](https://arxiv.org/abs/1906.06558v2)] Mask Based Unsupervised Content Transfer. [[pytorch](https://github.com/rmokady/mbu-content-tansfer)] [__`img.`__] :sunflower:

- [[ICLR](https://arxiv.org/abs/1906.07647)] Weakly Supervised Clustering by Exploiting Unique Class Count. [__`img.`__] :hospital:

- [[AAAI](https://arxiv.org/abs/1911.08039)] RRM: Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach. [[pytorch](https://github.com/zbf1991/RRM)] [__`img.`__] :star: :sunflower:

- [[AAAI](https://arxiv.org/abs/1811.10842)] CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation. [[mxnet](https://github.com/js-fan/CIAN)] [__`img.`__] :sunflower:

- [[AAAI](https://www.researchgate.net/publication/342540606_Learning_Saliency-Free_Model_with_Generic_Features_for_Weakly-Supervised_Semantic_Segmentation)] Learning Saliency-Free Model with Generic Features for Weakly-Supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[ACMM](https://dl.acm.org/doi/pdf/10.1145/3394171.3413652)] Weakly Supervised Segmentation with Maximum Bipartite Graph Matching. [__`img.`__] :sunflower:

- [[IJCAI](https://www.ijcai.org/Proceedings/2020/0120.pdf)] Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings. [__`img.`__] :sunflower:

- [[ICASSP](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9053384)] Weakly Supervised Semantic Segmentation For Remote Sensing Hyperspectral Imaging. [__`img.`__] :sunflower:

- [[IJCV](https://arxiv.org/abs/2002.08098)] Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning. [__`img.`__] :sunflower:

- [[IJCV](https://arxiv.org/abs/1912.11186v1)] A Comprehensive Analysis of Weakly-Supervised Semantic

Segmentation in Different Image Domains. [[tensorflow](https://github.com/lyndonchan/wsss-analysis)] [__`img.`__] :star: :hospital:

- [[TPAMI](https://ieeexplore.ieee.org/document/9193980)]Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation. [__`img.`__,__`ins.`__] :sunflower:

- [[TIP](https://arxiv.org/abs/1904.09092)] Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes. [__`box.`__,__`pan.`__] :sunflower:

- [[TMI](https://arxiv.org/abs/2007.05448)] Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images. [__`img.`__] :hospital:

- [[NN](https://arxiv.org/abs/1908.05770)] Discretely-constrained Deep Network for Weakly Supervised Segmentation. [__`img.`__] :sunflower:

- [[IEEE Access](https://arxiv.org/abs/1910.05475)] SGAN: Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic Segmentation. [[pytorch](https://github.com/yaoqi-zd/SGAN)] [__`img.`__] :star: :sunflower:

- [[arXiv](https://arxiv.org/abs/2002.08254)] Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping -- Challenges and Opportunities. [__`img.`__] :earth_americas:

- [[arXiv](https://arxiv.org/abs/2001.11207)] Weakly Supervised Instance Segmentation by Deep Community Learning. [__`img.`__,__`ins.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1802.02212)] Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach. [__`img.`__] :hospital:

- [[arXiv](https://arxiv.org/abs/2001.09174)] Weakly Supervised Lesion Co-segmentation on CT Scans. [__`img.`__] :hospital:

- [[arXiv](https://arxiv.org/abs/1812.04831v1)] Weakly Supervised Instance Segmentation Using Hybrid Networks. [__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/2006.07834)] Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation. [__`img.`__] :sunflower:

---

## 2019

- [[CVPR](https://arxiv.org/pdf/1904.11693.pdf)] Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation. [__`box.`__] :sunflower:

- [[CVPR](https://arxiv.org/pdf/1902.10421.pdf)] FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference. [__`img.`__] :star: :sunflower:

- [[CVPR](https://arxiv.org/pdf/1904.05044.pdf)] IRNet: Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations. [[pytorch](https://github.com/jiwoon-ahn/irn)] [__`img.`__,__`ins.`__] :star: :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_CVPR_2019/papers/Shen_Cyclic_Guidance_for_Weakly_Supervised_Joint_Detection_and_Segmentation_CVPR_2019_paper.pdf)] Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation. [[pytorch](https://github.com/shenyunhang/WS-JDS)][__`img.`__] :sunflower: 

- [[CVPR](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Learning_Instance_Activation_Maps_for_Weakly_Supervised_Instance_Segmentation_CVPR_2019_paper.pdf)] Learning Instance Activation Maps for Weakly Supervised Instance Segmentation. [__`img.`__,__`ins.`__] :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhou_Collaborative_Learning_of_Semi-Supervised_Segmentation_and_Classification_for_Medical_Images_CVPR_2019_paper.pdf)] Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images. [__`img.`__]  :hospital:

- [[CVPR](https://arxiv.org/abs/1905.01298.pdf)] SCOPS: Self-Supervised Co-Part Segmentation. [[pytorch](https://github.com/NVlabs/SCOPS)][__`img.`__] :sunflower:

- [[CVPRW](https://arxiv.org/abs/1905.05880)] Budget-aware Semi-Supervised Semantic and Instance Segmentation. [__`img.`__] :sunflower:

- [[NIPS](http://papers.nips.cc/paper/8885-weakly-supervised-instance-segmentation-using-the-bounding-box-tightness-prior.pdf)] Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior. [[pytorch](https://github.com/chengchunhsu/WSIS_BBTP)][__`box.`__,__`ins`__]:sunflower:

- [[ICCV](https://arxiv.org/abs/1909.04161)] JSWS: Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation. [[pytorch](https://github.com/zengxianyu/jsws)][__`img.`__] :star: :sunflower:

- [[ICCV](https://arxiv.org/abs/1911.01370)] SSDD: Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation. [[pytorch](https://github.com/shimoda-uec/ssdd)][__`img.`__] :star: :sunflower:

- [[ICCV](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chan_HistoSegNet_Semantic_Segmentation_of_Histological_Tissue_Type_in_Whole_Slide_ICCV_2019_paper.pdf)] HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide Images. [[tensorflow](https://github.com/lyndonchan/hsn_v1)][__`img.`__] :star: :hospital:

- [[ICCV](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9009076)] Integral Object Mining via Online Attention Accumulation. [[pytorch](https://github.com/PengtaoJiang/OAA)][[pytorch_v2](https://github.com/PengtaoJiang/OAA-PyTorch)][__`img.`__] :sunflower:

- [[ICCV](https://arxiv.org/abs/1908.04501)] Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[ICCV](https://arxiv.org/abs/1908.07669)] Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation.  [[pytorch](https://github.com/JiahuaDong/ICCV2019Publication-Semantic-Transferable-Weakly-Supervised-Endoscopic-Lesions-Segmentation)][__`img.`__] :hospital:

- [[ICCV](https://arxiv.org/abs/1910.02624)] Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation. [__`img.`__,__`ins.`__] :sunflower:

- [[ICCVW](https://arxiv.org/abs/1912.08936)] One-Shot Weakly Supervised Video Object Segmentation. [__`vid.`__] :sunflower:

- [[IJCAI](https://www.researchgate.net/publication/334844257_Boundary_Perception_Guidance_A_Scribble-Supervised_Semantic_Segmentation_Approach)] Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach. [__`box.`__]  :sunflower:

- [[AAAI](https://www.aaai.org/ojs/index.php/AAAI/article/view/3860)] Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis. [__`img.`__] :hospital: 

- [[AAAI](https://arxiv.org/pdf/1807.11719.pdf)] A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels. [__`img.`__] :hospital: 

- [[WACV](https://arxiv.org/abs/1705.01262)] Learning to segment with image-level supervision. [__`img.`__] :sunflower: 

- [[MICCAI](https://arxiv.org/abs/1911.02014)] Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation. [__`img.`__] :hospital: 

- [[MICCAI](https://arxiv.org/abs/1910.01236)] Weakly Supervised Segmentation from Extreme Points. [__`img.`__] :hospital: 

- [[MICCAI](https://arxiv.org/abs/1911.13077)] Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response. [[pytorch](https://github.com/naivete5656/WSISPDR)][__`img.`__,__`ins.`__] :hospital: 

- [[ICIP](https://arxiv.org/abs/2001.11248)] Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized Lp Norm. [__`img.`__] :hospital: 

- [[ICMLA](https://arxiv.org/abs/1911.01738)] Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem. [__`img.`__] :hospital: 

- [[TIP](https://arxiv.org/abs/1804.04882)] Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation. [[caffe](https://github.com/gramuah/weakly-supervised-segmentation)] [__`img.`__] :star: :sunflower:

- [[TMM](https://ieeexplore.ieee.org/document/8705324),[arXiv](https://arxiv.org/abs/1803.02563)] Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation [__`img.`__] :sunflower:

- [[MIA](https://www.sciencedirect.com/science/article/pii/S1361841518306145?via%3Dihub)] Constrained-CNN losses for weakly supervised segmentation. [[pytorch](https://github.com/LIVIAETS/SizeLoss_WSS)][[caffe](https://github.com/meng-tang/rloss)] [__`img.`__] :star: :hospital:

- [[JURSE](https://arxiv.org/abs/1904.03983)] Weakly Supervised Semantic Segmentation of Satellite Images. [__`img.`__] :earth_americas:

- [[arXiv](https://arxiv.org/abs/1909.03714)] SSENet: Self-supervised Scale Equivariant Network for Weakly Supervised Semantic Segmentation. [[pytorch](https://github.com/YudeWang/SSENet-pytorch)] [__`img.`__] :star: :sunflower:

- [[arXiv](https://arxiv.org/abs/1905.12190)] Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation [__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1906.04651)] Gated CRF Loss for Weakly Supervised Semantic Image Segmentation [[pytorch](https://github.com/LEONOB2014/GatedCRFLoss)][__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1904.01749)] Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues. [__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1910.12326)] Weakly Supervised Multi-Task Learning for Cell Detection and Segmentation. [__`img.`__] :hospital:

---

## 2018

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/0812.pdf)] MDC: Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation. [__`img.`__] :star: :sunflower:

- [[CVPR](http://zpascal.net/cvpr2018/Huang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf)] DSRG: Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing. [[caffe](https://github.com/speedinghzl/DSRG)][[tensorflow](https://github.com/xtudbxk/DSRG-tensorflow)] [__`img.`__] :star: :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Bootstrapping_the_Performance_CVPR_2018_paper.pdf)] Bootstrapping the Performance of Webly Supervised Semantic Segmentation. [[caffe](https://github.com/ascust/BDWSS)] [__`img.`__]  :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Weakly_Supervised_Instance_CVPR_2018_paper.pdf)] Weakly Supervised Instance Segmentation using Class Peak Response.  [[pytorch](https://github.com/ZhouYanzhao/PRM)][__`img.`__,__`ins.`__] :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ge_Multi-Evidence_Filtering_and_CVPR_2018_paper.pdf)] Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning. [__`img.`__] :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf)] Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features. [__`img.`__] :sunflower: 

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tang_Normalized_Cut_Loss_CVPR_2018_paper.pdf)] Normalized Cut Loss for Weakly-Supervised CNN Segmentation. [__`img.`__] :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ahn_Learning_Pixel-Level_Semantic_CVPR_2018_paper.pdf)] PSA: Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation. [[pytorch](https://github.com/jiwoon-ahn/psa)] [__`img.`__] :star: :sunflower:

- [[CVPR](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ding_Weakly-Supervised_Action_Segmentation_CVPR_2018_paper.pdf)] Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment. [__`box.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/1802.10171)] Tell Me Where to Look: Guided Attention Inference Network. [__`img.`__] :sunflower:

- [[AAAI](https://arxiv.org/pdf/1711.06828.pdf)] Transferable Semi-supervised Semantic Segmentation. [__`img.`__]  :sunflower:

- [[ECCV](https://arxiv.org/abs/1808.03575v3)] Weakly- and Semi-Supervised Panoptic Segmentation. [[matlab](https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation)][__`img.`__,__`ins.`__,__`pan.`__] :star: :sunflower:

- [[ECCV](https://arxiv.org/abs/1803.09569)] On Regularized Losses for Weakly-supervised CNN Segmentation[__`img.`__] :sunflower:

- [[BMVC](https://arxiv.org/abs/1807.09169)] CSPN: Convolutional Simplex Projection Network for Weakly Supervised Semantic Segmentation. [[caffe](https://github.com/briqr/CSPN)][__`img.`__] :star: :sunflower:

- [[GCPR](https://arxiv.org/abs/1807.02001)] Acquire, Augment, Segment & Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products. [__`img.`__,__`ins.`__] :sunflower:

- [[TPAMI](https://arxiv.org/abs/1706.02189)] Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1808.01625)] Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models. [__`img.`__] :sunflower:

- [[arXiv](https://arxiv.org/abs/1810.07050)] Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation. [__`img.`__] :sunflower:



---

## 2017

- [[CVPR](https://arxiv.org/abs/1703.08448)] AE-PSL: Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach. [__`img.`__] :star: :sunflower:

- [[CVPR](http://webia.lip6.fr/~cord/pdfs/publis/Durand_WILDCAT_CVPR_2017.pdf)] WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation. [[pytorch](https://github.com/durandtibo/wildcat.pytorch)][__`img.`__] :star: :sunflower:

- [[CVPR](https://arxiv.org/abs/1701.00352)] Weakly Supervised Semantic Segmentation using Web-Crawled Videos. [__`img.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/1802.00470)] Learning Random-walk Label Propagation for Weakly-supervised Semantic Segmentation. [__`img.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/1703.08448)] Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach. [__`img.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/1605.02964)] Weakly Supervised Learning of Affordances. [__`img.`__] :sunflower:

- [[CVPR](https://arxiv.org/abs/1603.07485)] Simple Does It: Weakly Supervised Instance and Semantic Segmentation. [[tensorflow](https://github.com/johnnylu305/Simple-does-it-weakly-supervised-instance-and-semantic-segmentation)][__`img.`__,__`ins.`__] :sunflower:

- [[ICCV](https://arxiv.org/abs/1708.04400)] Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation. [__`vid.`__] :sunflower:

- [[ICCV](https://arxiv.org/abs/1703.09695)] Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network. [__`vid.`__] :sunflower:

- [[AAAI](https://pdfs.semanticscholar.org/9345/23b3de05318606d4f550f5828cf30a56b1d3.pdf?_ga=2.30714812.2026882509.1564975284-400067050.1564456907)] Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network. [__`img.`__] :sunflower:

- [[ICRA](https://arxiv.org/abs/1610.01238)] Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy. [__`img.`__,__`pan.`__] :sunflower:

- [[BMVC](https://arxiv.org/abs/1707.05821v1)] DCSP: Discovering Class Specific Pixels for Weakly Supervised Semantic Segmentation. [[tensorflow](https://github.com/arslan-chaudhry/dcsp_segmentation)][__`img.`__] :sunflower:

- [[BMVC](https://arxiv.org/abs/1705.09052)] Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation. [[mxnet](https://github.com/ascust/wsscoseg)][__`img.`__] :sunflower:

- [[ACCV](https://arxiv.org/abs/1606.02280)] Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. [__`vid.`__] :sunflower:

- [[TPAMI](https://weiyc.github.io/assets/pdf/stc_tpami.pdf)] STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation. [__`img.`__] :star: :sunflower:

- [[TPAMI](https://arxiv.org/abs/1710.01457)] Learning to Segment Human by Watching YouTube. [__`vid.`__] :sunflower:

- [[TPAMI](https://arxiv.org/abs/1708.02459)] Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes. [__`img.`__] :sunflower:

- [[TMI](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7971941),[arXiv](https://arxiv.org/abs/1701.00794)] Constrained Deep Weak Supervision for Histopathology Image Segmentation. [__`img.`__] :star: :hospital:

---

## 2016

- [[ECCV](https://arxiv.org/abs/1603.06098)] SEC: Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. [[caffe](https://github.com/kolesman/SEC)][[pytorch](https://github.com/halbielee/SEC_pytorch)][__`img.`__] :star: :sunflower:

- [[ECCV](https://hal.archives-ouvertes.fr/hal-01292794/document)] Weakly-Supervised Semantic Segmentation using Motion Cues. [__`vid.`__]  :sunflower:

- [[ECCV](http://img.cs.uec.ac.jp/pub/conf16/161011shimok_0.pdf)] Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation. [__`img.`__]  :earth_americas:

- [[ECCV](https://arxiv.org/abs/1609.00446)] Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation. [__`img.`__]  :sunflower:

- [[ICLR](https://arxiv.org/abs/1511.06309v5)] Spatio-temporal video autoencoder with differentiable memory. [[lua](https://github.com/viorik/ConvLSTM)][__`vid.`__] :sunflower: 

- [[EMMCVPR](https://arxiv.org/abs/1612.02101)] Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation. [__`img.`__]  :sunflower:

- [[TGRS](https://ieeexplore.ieee.org/abstract/document/7414501)] Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning [__`img.`__]  :earth_americas:

- [[arXiv](https://arxiv.org/abs/1612.02766)] Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation. [__`img.`__]  :earth_americas:

- [[arXiv](https://arxiv.org/abs/1602.04984)] Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation. [__`img.`__]  :hospital:



---



## 2015

- [[ICCV](https://arxiv.org/abs/1506.03648)] CCNN: Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. [[caffe](https://github.com/pathak22/ccnn)][__`img.`__] :star: :sunflower:

- [[ICCV](https://arxiv.org/abs/1502.02734v3)] Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation. [[caffe](https://github.com/TheLegendAli/DeepLab-Context)][[caffe_v2](https://github.com/open-cv/deeplab-v1)][__`img.`__] :star: :sunflower: