This repository contains lists of state-or-art weakly supervised semantic segmentation works. Papers and resources are listed below according to supervision types.
There are some personal views and notes, just ignore if not interested. (keep updating)
- Paper list
- instance
- box
- one-shot
- others
- Resources
some unsupervised segment proposal methods and datasets here.
CVPR 2018 Tutorial : WSL web&ppt, Part1 ,Part2
No | Supervision | Difficulty | Domain | Core issues |
---|---|---|---|---|
1 | Bounding box | middle | annotated classes | transfer learning |
2 | One-shot segment | middle | similar objects | one-shot learning |
3 | Image/video label | hard | annotated classes | transfer learning |
4 | Others | n/a | n/a | n/a |
Instance semantic segmentation
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Learning to Segment Every Thing, CVPR 2018
:Learning weight transfer from well-annotated subset, transfer class-specific weights(output layers) from detection and classification branch, based on Mask-RCNN
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Pseudo Mask Augmented Object Detection, CVPR 2018
:State-of-art weakly supervised instance segmentation with bounding box annotation. EM optimizes pseudo mask and segmentation parameter like Boxsup. Graphcut on superpixel is employed to refine pseudo mask.
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Simple Does It: Weakly Supervised Instance and Semantic Segmentation, CVPR 2017 [web] [ref-code][supp]
:Grabcut+(HED bounday) and MCG , train foreground segmentation network directly with generated mask semantic segmentaion, sensitive to env(quality) of training images. Check my implementation for pseudo mask generation which is similar to Grabcut+ MCG. But it can't match the performance discribed in paper sup. Opencv version Grabcut perform even worse.
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Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation, ICCV 2015
:Based on CRF refine, EM seems not work
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BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation, ICCV 2015
:Iteratively update parameters and region proposal labels, proposals are selected by network output masks
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Deepcut: Object segmentation from bounding box annotations using convolutional neural networks, TMI 2017
Arxiv paper
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Learning to Segment via Cut-and-Paste, Arxiv 1803
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Adversarial Learning for Semi-Supervised Semantic Segmentation, Arxiv1802, [code]
DAVIS Challenge: http://davischallenge.org/
: Davis17/18(Semi-supervised Video segmentation task), Davis16 is video salient object segmentation without the first frame annotations.
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Fast and Accurate Online Video Object Segmentation via Tracking Parts, CVPR 2018(Spotlight) [code]
:state-of-art, 82.4%/1.8s 77.9%/0.6s
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OSVOS: One-Shot Video Object Segmentation, CVPR 2017 [web][code]
:milestone, fine-tuning parent network with the first frame mask, 79.8%/10s
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Self-produced Guidance for Weakly-supervised Object Localization, ECCV 2018
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Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation, BMVC 2018
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Weakly Supervised Instance Segmentation using Class Peak Response, CVPR 2018(Spotlight)
:state-of-art practice for instance seg with only class label.
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Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features, CVPR 2018
:Superpixel-> RegionNet(RoI classfier)-> Saliency refine, iteratively update with PixelNet(FCN)
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Revisiting Dilated Convolution: A Simple Approach for Weakly- and SemiSupervised Semantic Segmentation, CVPR 2018(Spotlight)
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Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing, CVPR 2018 [web][code]
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Adversarial Complementary Learning for Weakly Supervised Object Localization, CVPR 2018
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Weakly Supervised Semantic Segmentation using Web-Crawled Videos, CVPR 2017(Spotlight) [web]
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WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation, CVPR 2017 [web][code]
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Learning random-walk label propagation for weakly-supervised semantic segmentation, CVPR 2017(Oral)
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Combining Bottom-Up, Top-Down, and Smoothness Cues for Weakly Supervised Image Segmentation, CVPR 2017
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Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network, AAAI 2017
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Learning from Weak and Noisy Labels for Semantic Segmentation, PAMI 2017
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Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation, ECCV 2016 [code]
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Backtracking ScSPM Image Classifier for Weakly Supervised Top-down Saliency, CVPR 2016, TIP 2018 Version
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Constrained Convolutional Neural Networks for Weakly Supervised Segmentation, ICCV 2015 [code]
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From Image-level to Pixel-level Labeling with Convolutional Networks, CVPR 2015
Resource
- Yunchao Wei talk in Chinese about WSL with image label
Arxiv paper
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Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation, Arxiv1804
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Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks, Arxiv 1711
Propagate method | Papers |
---|---|
Global Max Pooling(GMP) | Is object localization for free? - Weakly-supervised learning with convolutional neural networks,CVPR 2015 |
Global Average Pooling(GAP) | Learning Deep Features for Discriminative Localization CVPR 2016 |
Log-sum-exponential Pooling(LSE) | ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks,CVPR 2016 |
Global Weighted Rank Pooling(GWRP) | SEC ECCV 2016 |
Global rank Max-Min Pooling(GRP) | WILDCAT, CVPR 2017 |
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Weakly Supervised Region Proposal Network and Object Detection, ECCV 2018
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TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection, ECCV 2018
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Zigzag Learning for Weakly Supervised Object Detection, CVPR 2018
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W2F: A Weakly-Supervised to Fully-Supervised Framework for Object Detection, CVPR 2018
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Generative Adversarial Learning Towards Fast Weakly Supervised Detection, CVPR 2018
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Min-Entropy Latent Model for Weakly Supervised Object Detection, CVPR 2018
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Weakly Supervised Cascaded Convolutional Networks, CVPR 2017
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Multiple Instance Detection Network with Online Instance Classifier Refinement, CVPR 2017 [code]
- Deep Extreme Cut: From Extreme Points to Object Segmentation, CVPR 2018 [web][code]
- What's the Point: Semantic Segmentation with Point Supervision, ECCV 2016 [web][code]
- Normalized Cut Loss for Weakly-supervised CNN Segmentation, CVPR 2018
- ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation, CVPR 2016
- Learning to segment under various forms of weak supervision, CVPR 2015
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PCL: Proposal Cluster Learning for Weakly Supervised Object Detection, Arxiv1807 [code]
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WebSeg: Learning Semantic Segmentation from Web Searches, Arxiv1803
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On Regularized Losses for Weakly-supervised CNN Segmentation, Arxiv1803
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Weakly-Supervised Action Segmentation with Iterative Soft Boundary Assignment, CVPR 2018
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Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation, CVPR 2018
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Weakly Supervised Salient Object Detection Using Image Labels, AAAI 2018
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Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset, Arxiv 1803
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Learning Semantic Segmentation with Diverse Supervision, WACV 2018
If some related works are missed, please kindly notice me by dxzhang@zju.edu.cn