Unimatch v2: Pushing the limit of semi-supervised semantic segmentation
Semi-supervised semantic segmentation (SSS) aims at learning rich visual knowledge from
cheap unlabeled images to enhance semantic segmentation capability. Among recent …
cheap unlabeled images to enhance semantic segmentation capability. Among recent …
Triplet adaptation framework for robust semi-supervised learning
Semi-supervised learning (SSL) suffers from severe performance degradation when labeled
and unlabeled data come from inconsistent and imbalanced distribution. Nonetheless, there …
and unlabeled data come from inconsistent and imbalanced distribution. Nonetheless, there …
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
Pre-trained vision-language models (eg, CLIP) have shown powerful zero-shot transfer
capabilities. But they still struggle with domain shifts and typically require labeled data to …
capabilities. But they still struggle with domain shifts and typically require labeled data to …
Self-supervised Preference Optimization: Enhance Your Language Model with Preference Degree Awareness
Recently, there has been significant interest in replacing the reward model in Reinforcement
Learning with Human Feedback (RLHF) methods for Large Language Models (LLMs), such …
Learning with Human Feedback (RLHF) methods for Large Language Models (LLMs), such …