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This repository contains lists of state-or-art weakly supervised semantic segmentation works

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Weakly Supervised Semantic Segmentation list

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.

Last update 2019/2

  • Paper list
    • instance
    • box
    • one-shot
    • others
  • Resources

some unsupervised segment proposal methods and datasets here.

CVPR 2018 Tutorial : WSL web&ppt, Part1 ,Part2

Typical weak supervised segmentation problems

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

1.Bounding box supervision

Instance semantic segmentation

git

  • 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

  • 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.

git2

Arxiv paper

2.One-Shot segmentation supervision

DAVIS Challenge: http://davischallenge.org/

: Davis17/18(Semi-supervised Video segmentation task), Davis16 is video salient object segmentation without the first frame annotations.

git2

3.Image/video label supervision

prm

Resource

Arxiv paper

3.1 Deep activation

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

3.2 Weakly supervised Detection / Localization(TODO)

4.Other supervision

Points

Scribbles

5.Close Related or unpublished work

If some related works are missed, please kindly notice me by dxzhang@zju.edu.cn

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