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Semi-Supervised Semantic Segmentation

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보존된 평가 기록: 438

Models that are trained with a small number of labeled examples and a large number of unlabeled examples and whose aim is to learn to segment an image (i.e. assign a class to every pixel).

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/1181110317/SSL_CTT

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Semi-Supervised Semantic Segmentation with Cross Teacher Training

https://github.com/Britefury/cutmix-semisup-seg

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Semi-supervised semantic segmentation needs strong, varied perturbations

https://github.com/CVMI-Lab/DARS

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Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation

https://github.com/CuriousAI/mean-teacher

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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

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/Haochen-Wang409/U2PL

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Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

https://github.com/HiLab-git/SSL4MIS

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Triple-View Feature Learning for Medical Image Segmentation

https://github.com/Ivan1248/semisup-seg-efficient

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Revisiting consistency for semi-supervised semantic segmentation

https://github.com/Jin-Ying/GTA-Seg

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Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant

https://github.com/LIVIAETS/semi_curriculum

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Curriculum semi-supervised segmentation

https://github.com/LiheYoung/ST-PlusPlus

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ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation

https://github.com/LiheYoung/UniMatch

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Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation

https://github.com/LiheYoung/UniMatch-V2

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UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation

https://github.com/RK621/ThreeStageSelftraining_SemanticSegmentation

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A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation

https://github.com/Shathe/SemiSeg-Contrastive

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Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank

https://github.com/WilhelmT/ClassMix

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ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning

https://github.com/Xiangyi1996/PPNet-PyTorch

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Part-aware Prototype Network for Few-shot Semantic Segmentation

https://github.com/ZHKKKe/PixelSSL

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Guided Collaborative Training for Pixel-wise Semi-Supervised Learning

https://github.com/abj247/pv-s3

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PV-S3: Advancing Automatic Photovoltaic Defect Detection using Semi-Supervised Semantic Segmentation of Electroluminescence Images

https://github.com/angeloucn/min_max_similarity

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Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation

https://github.com/arnab39/FewShot_GAN-Unet3D

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Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

https://github.com/azhuantou/aiscene

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Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation

https://github.com/bbbbchan/corrmatch

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CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation

https://github.com/cao-cong/ads-semiseg

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Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation

https://github.com/charlesCXK/TorchSemiSeg

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Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

https://github.com/christmasfan/ssl_denoising_segmentation

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Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic Segmentation

https://github.com/cv-rits/coarse3d

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COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentation

https://github.com/cvlab-stonybrook/Weighting-Pseudo-Labels

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Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation

https://github.com/cvlab-stonybrook/beyond-pixels

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Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier

https://github.com/dayan-guan/usrn

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Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentation

https://github.com/deepmed-lab-ecnu/bcp

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Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation

https://github.com/djh-dzxw/brpg

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Boundary-Refined Prototype Generation: A General End-to-End Paradigm for Semi-Supervised Semantic Segmentation

https://github.com/dvlab-research/Context-Aware-Consistency

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Semi-supervised Semantic Segmentation with Directional Context-aware Consistency

https://github.com/earth-insights/semi-supervised-semantic-segmentation-with-distillation

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RS-MTDF: Multi-Teacher Distillation and Fusion for Remote Sensing Semi-Supervised Semantic Segmentation

https://github.com/gavinwxy/ddfp

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Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation

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