25 citations · 91 across the 19 of their papers we have counts for
4 papers · 1 filter
ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness
Yijun Liang, Ming Li, Chenrui Fan +7
Color plays an important role in human perception and usually provides critical clues in visual reasoning. However, it is unclear whether and how vision-language models (VLMs) can…
Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion
Jiuhai Chen, Jianwei Yang, Haiping Wu +4
We present Florence-VL, a new family of multimodal large language models (MLLMs) with enriched visual representations produced by Florence-2, a generative vision foundation model.…
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement
Xiyao Wang, Jiuhai Chen, Zhaoyang Wang +8
Large vision-language models (LVLMs) have achieved impressive results in visual question-answering and reasoning tasks through vision instruction tuning on specific datasets. Howev…
Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
Jiuhai Chen, Chen Zhu, Bin Dai
Self-supervised learning (SSL) has achieved great success in a variety of computer vision tasks. However, the mechanism of how SSL works in these tasks remains a mystery. In this p…