Zobrazeno 1 - 10
of 219
pro vyhledávání: '"Zhang, Erli"'
Surgical video segmentation is a critical task in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2 (SAM2) framework has shown superior advancements in image and video s
Externí odkaz:
http://arxiv.org/abs/2408.07931
Autor:
Wu, Haoning, Zhu, Hanwei, Zhang, Zicheng, Zhang, Erli, Chen, Chaofeng, Liao, Liang, Li, Chunyi, Wang, Annan, Sun, Wenxiu, Yan, Qiong, Liu, Xiaohong, Zhai, Guangtao, Wang, Shiqi, Lin, Weisi
Comparative settings (e.g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardizes the evaluation criteria across different observers and offer more
Externí odkaz:
http://arxiv.org/abs/2402.16641
The rapid development of Multi-modality Large Language Models (MLLMs) has navigated a paradigm shift in computer vision, moving towards versatile foundational models. However, evaluating MLLMs in low-level visual perception and understanding remains
Externí odkaz:
http://arxiv.org/abs/2402.07116
Autor:
Wu, Haoning, Zhang, Zicheng, Zhang, Weixia, Chen, Chaofeng, Liao, Liang, Li, Chunyi, Gao, Yixuan, Wang, Annan, Zhang, Erli, Sun, Wenxiu, Yan, Qiong, Min, Xiongkuo, Zhai, Guangtao, Lin, Weisi
The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents. While recent studies have demonstrated the exceptional potentials of la
Externí odkaz:
http://arxiv.org/abs/2312.17090
Autor:
Zhang, Zicheng, Wu, Haoning, Ji, Zhongpeng, Li, Chunyi, Zhang, Erli, Sun, Wei, Liu, Xiaohong, Min, Xiongkuo, Sun, Fengyu, Jui, Shangling, Lin, Weisi, Zhai, Guangtao
Recent advancements in Multi-modality Large Language Models (MLLMs) have demonstrated remarkable capabilities in complex high-level vision tasks. However, the exploration of MLLM potential in visual quality assessment, a vital aspect of low-level vis
Externí odkaz:
http://arxiv.org/abs/2312.15300
Autor:
Wu, Haoning, Zhang, Zicheng, Zhang, Erli, Chen, Chaofeng, Liao, Liang, Wang, Annan, Xu, Kaixin, Li, Chunyi, Hou, Jingwen, Zhai, Guangtao, Xue, Geng, Sun, Wenxiu, Yan, Qiong, Lin, Weisi
Multi-modality foundation models, as represented by GPT-4V, have brought a new paradigm for low-level visual perception and understanding tasks, that can respond to a broad range of natural human instructions in a model. While existing foundation mod
Externí odkaz:
http://arxiv.org/abs/2311.06783
Autor:
Wu, Haoning, Zhang, Zicheng, Zhang, Erli, Chen, Chaofeng, Liao, Liang, Wang, Annan, Li, Chunyi, Sun, Wenxiu, Yan, Qiong, Zhai, Guangtao, Lin, Weisi
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
Externí odkaz:
http://arxiv.org/abs/2309.14181
Autor:
Wu, Haoning, Zhang, Erli, Liao, Liang, Chen, Chaofeng, Hou, Jingwen, Wang, Annan, Sun, Wenxiu, Yan, Qiong, Lin, Weisi
The proliferation of in-the-wild videos has greatly expanded the Video Quality Assessment (VQA) problem. Unlike early definitions that usually focus on limited distortion types, VQA on in-the-wild videos is especially challenging as it could be affec
Externí odkaz:
http://arxiv.org/abs/2305.12726
Autor:
Wu, Haoning, Liao, Liang, Hou, Jingwen, Chen, Chaofeng, Zhang, Erli, Wang, Annan, Sun, Wenxiu, Yan, Qiong, Lin, Weisi
Recent learning-based video quality assessment (VQA) algorithms are expensive to implement due to the cost of data collection of human quality opinions, and are less robust across various scenarios due to the biases of these opinions. This motivates
Externí odkaz:
http://arxiv.org/abs/2302.13269
Autor:
Wu, Haoning, Zhang, Erli, Liao, Liang, Chen, Chaofeng, Hou, Jingwen, Wang, Annan, Sun, Wenxiu, Yan, Qiong, Lin, Weisi
The rapid increase in user-generated-content (UGC) videos calls for the development of effective video quality assessment (VQA) algorithms. However, the objective of the UGC-VQA problem is still ambiguous and can be viewed from two perspectives: the
Externí odkaz:
http://arxiv.org/abs/2211.04894