/Awesome-SSL

Semi-supervised Learning

Semi-supervised Learning

Content

ICCV 2023

  • Point2Mask Point-supervised Panoptic Segmentation via Optimal Transport [note](ICCV 2023/Point2Mask Point-supervised Panoptic Segmentation via Optimal Transport.md)

NeurIPS 2023

  • A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

  • Semi-Supervised Domain Generalization with Known and Unknown Classes

  • Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

  • Topology-Aware Uncertainty for Image Segmentation

  • Structured Neural Networks for Density Estimation and Causal Inference

  • Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations

  • Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation

  • Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection

  • Characterizing the Impacts of Semi-supervised Learning for Weak Supervision

  • Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning

  • Switching Temporary Teachers for Semi-Supervised Semantic Segmentation

  • Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition

  • Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation

  • Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering

  • DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation

  • Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation

  • Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

  • FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning

  • Beyond probability partitions: Calibrating neural networks with semantic aware grouping

  • All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation

  • Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

  • S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

  • Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration

  • Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport

  • InstanT: Semi-supervised Learning with Instance-dependent Thresholds

  • Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning

  • Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning