Preview WB-DH: Towards Whole Body Digital Human Bench for the Generation of Whole-body Talking Avatar Videos
Fuente:
arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918123840471040 |
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| author | Wang, Chaoyi Yang, Yifan Pei, Jun Xia, Lijie Liu, Jianpo Yuan, Xiaobing Di, Xinhan |
| author_facet | Wang, Chaoyi Yang, Yifan Pei, Jun Xia, Lijie Liu, Jianpo Yuan, Xiaobing Di, Xinhan |
| contents | Creating realistic, fully animatable whole-body avatars from a single portrait is challenging due to limitations in capturing subtle expressions, body movements, and dynamic backgrounds. Current evaluation datasets and metrics fall short in addressing these complexities. To bridge this gap, we introduce the Whole-Body Benchmark Dataset (WB-DH), an open-source, multi-modal benchmark designed for evaluating whole-body animatable avatar generation. Key features include: (1) detailed multi-modal annotations for fine-grained guidance, (2) a versatile evaluation framework, and (3) public access to the dataset and tools at https://github.com/deepreasonings/WholeBodyBenchmark. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_08891 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Preview WB-DH: Towards Whole Body Digital Human Bench for the Generation of Whole-body Talking Avatar Videos Wang, Chaoyi Yang, Yifan Pei, Jun Xia, Lijie Liu, Jianpo Yuan, Xiaobing Di, Xinhan Computer Vision and Pattern Recognition Creating realistic, fully animatable whole-body avatars from a single portrait is challenging due to limitations in capturing subtle expressions, body movements, and dynamic backgrounds. Current evaluation datasets and metrics fall short in addressing these complexities. To bridge this gap, we introduce the Whole-Body Benchmark Dataset (WB-DH), an open-source, multi-modal benchmark designed for evaluating whole-body animatable avatar generation. Key features include: (1) detailed multi-modal annotations for fine-grained guidance, (2) a versatile evaluation framework, and (3) public access to the dataset and tools at https://github.com/deepreasonings/WholeBodyBenchmark. |
| title | Preview WB-DH: Towards Whole Body Digital Human Bench for the Generation of Whole-body Talking Avatar Videos |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2508.08891 |