Q-bench: a benchmark for general-purpose foundation models on low-level vision

• Main Authors: Wu, Haoning, Zhang, Zicheng, Zhang, Erli, Chen, Chaofeng, Liao, Liang, Wang, Annan, Li, Chunyi, Sun, Wenxiu, Yan, Qiong, Zhai, Guangtao, Lin, Weisi
• Other Authors: College of Computing and Data Science
• Format: Conference or Workshop Item
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Multi-modality large language models; Computer vision
• Online Access: https://hdl.handle.net/10356/178462; http://arxiv.org/abs/2309.14181v3; https://openreview.net/forum?id=0V5TVt9bk0; https://iclr.cc/
• Institution: Nanyang Technological University

The rapid evolution of Multi-modality Large Language Models (MLLMs) has catalyzed a shift in computer vision from specialized models to general-purpose foundation models. Nevertheless, there is still an inadequacy in assessing the abilities of MLLMs on low-level visual perception and understandin...