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pro vyhledávání: '"Wu, Haoning"'
Autor:
Wu, Siwei, Zhu, Kang, Bai, Yu, Liang, Yiming, Li, Yizhi, Wu, Haoning, Liu, J. H., Liu, Ruibo, Qu, Xingwei, Cheng, Xuxin, Zhang, Ge, Huang, Wenhao, Lin, Chenghua
Given the remarkable success that large visual language models (LVLMs) have achieved in image perception tasks, the endeavor to make LVLMs perceive the world like humans is drawing increasing attention. Current multi-modal benchmarks primarily focus
Externí odkaz:
http://arxiv.org/abs/2407.17379
Large multimodal models (LMMs) are processing increasingly longer and richer inputs. Albeit the progress, few public benchmark is available to measure such development. To mitigate this gap, we introduce LongVideoBench, a question-answering benchmark
Externí odkaz:
http://arxiv.org/abs/2407.15754
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:
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