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Weakly-Supervised Semantic Segmentation

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The semantic segmentation task is to assign a label from a label set to each pixel in an image. In the case of fully supervised setting, the dataset consists of images and their corresponding pixel-level class-specific annotations (expensive pixel-level annotations). However, in the weakly-supervised setting, the dataset consists of images and corresponding annotations that are relatively easy to obtain, such as tags/labels of objects present in the image.

<span style="color:grey; opacity: 0.6">( Image credit: Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/deeplab/deeplab-public

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Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation

https://github.com/AIGeeksGroup/DOEI

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DOEI: Dual Optimization of Embedding Information for Attention-Enhanced Class Activation Maps

https://github.com/Big-Brother-Pikachu/Text2Mask

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From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models

https://github.com/DesertsP/SLRNet

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Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation

https://github.com/ErikStammes/EADER

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Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation

https://github.com/Ferenas/CPN

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Complementary Patch for Weakly Supervised Semantic Segmentation

https://github.com/GuoleiSun/MCIS_wsss

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Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation

https://github.com/HAL-42/FMA-WSSS

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Foundation Model Assisted Weakly Supervised Semantic Segmentation

https://github.com/Juliachang/SC-CAM

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Weakly-Supervised Semantic Segmentation via Sub-category Exploration

https://github.com/LIVIAETS/SizeLoss_WSS

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Constrained-CNN losses for weakly supervised segmentation

https://github.com/Lixy1997/Group-WSSS

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Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

https://github.com/NUST-Machine-Intelligence-Laboratory/nsrom

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Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation

https://github.com/OFRIN/PuzzleCAM

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Puzzle-CAM: Improved localization via matching partial and full features

https://github.com/QingyongHu/SQN

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SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds

https://github.com/Vious/LPG_BBox_Segmentation

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Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation

https://github.com/Xavier-Pan/WSGCN

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Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks

https://github.com/YininKorea/FBR

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Fine-grained Background Representation for Weakly Supervised Semantic Segmentation

https://github.com/YudeWang/SEAM

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Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

https://github.com/YudeWang/SSENet-pytorch

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Self-supervised Scale Equivariant Network for Weakly Supervised Semantic Segmentation

https://github.com/arslan-chaudhry/dcsp_segmentation

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Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation

https://github.com/arvijj/hfpl

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High-fidelity Pseudo-labels for Boosting Weakly-Supervised Segmentation

https://github.com/arvijj/icam

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Importance Sampling CAMs for Weakly-Supervised Segmentation

https://github.com/barrett-python/cpal

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Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic Segmentation

https://github.com/barrett-python/sfc

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SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation

https://github.com/bharathprabakaran/boundarycam

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ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images

https://github.com/bharathprabakaran/refit

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ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images

https://github.com/briqr/CSPN

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Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation

https://github.com/bupt-ai-cz/SMAF

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A Self-Training Framework Based on Multi-Scale Attention Fusion for Weakly Supervised Semantic Segmentation

https://github.com/bupt-ai-cz/wuda

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WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels

https://github.com/catalinatan/spars

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SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver Tumours

https://github.com/cenkbircanoglu/isim

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ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation

https://github.com/chenqi1126/sipe

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Self-supervised Image-specific Prototype Exploration for Weakly Supervised Semantic Segmentation

https://github.com/chohoonhee/ev-wsss

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Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event Cameras

https://github.com/chuhan89/wsss-tissue

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Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels

https://github.com/chunmengliu1/mecpformer

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MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic Segmentation

https://github.com/chunyanwang1/ws-fcn

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Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation

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