5 papers
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement
Yuqi Lin, Hengjia Li, Wenqi Shao +5
In this paper, we explore a principal way to enhance the quality of widely pre-existing coarse masks, enabling them to serve as reliable training data for segmentation models to re…
Enhance-A-Video: Better Generated Video for Free
Yang Luo, Xuanlei Zhao, Mengzhao Chen +5
DiT-based video generation has achieved remarkable results, but research into enhancing existing models remains relatively unexplored. In this work, we introduce a training-free ap…
B-AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Black-box Adversarial Visual-Instructions
Hao Zhang, Wenqi Shao, Hong Liu +5
Large Vision-Language Models (LVLMs) have shown significant progress in responding well to visual-instructions from users. However, these instructions, encompassing images and text…
Prioritize Alignment in Dataset Distillation
Zekai Li, Ziyao Guo, Wangbo Zhao +8
Dataset Distillation aims to compress a large dataset into a significantly more compact, synthetic one without compromising the performance of the trained models. To achieve this,…
Open-Vocabulary Animal Keypoint Detection with Semantic-feature Matching
Hao Zhang, Lumin Xu, Shenqi Lai +5
Current image-based keypoint detection methods for animal (including human) bodies and faces are generally divided into full-supervised and few-shot class-agnostic approaches. The…