Zobrazeno 1 - 10
of 570
pro vyhledávání: '"CHEN Bolin"'
Autor:
Chen, Bolin, Ye, Yan, Chen, Jie, Liao, Ru-Ling, Yin, Shanzhi, Wang, Shiqi, Yang, Kaifa, Li, Yue, Xu, Yiling, Wang, Ye-Kui, Gehlot, Shiv, Su, Guan-Ming, Yin, Peng, McCarthy, Sean, Sullivan, Gary J.
This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representations of a face video signal (i.e., 2D/3D key-points, facial semantics
Externí odkaz:
http://arxiv.org/abs/2410.15105
In this paper, we propose a novel Multi-granularity Temporal Trajectory Factorization framework for generative human video compression, which holds great potential for bandwidth-constrained human-centric video communication. In particular, the propos
Externí odkaz:
http://arxiv.org/abs/2410.10171
This paper proposes to learn generative priors from the motion patterns instead of video contents for generative video compression. The priors are derived from small motion dynamics in common scenes such as swinging trees in the wind and floating boa
Externí odkaz:
http://arxiv.org/abs/2410.09768
Autor:
Chen, Bolin, Yin, Shanzhi, Zhang, Zihan, Chen, Jie, Liao, Ru-Ling, Zhu, Lingyu, Wang, Shiqi, Ye, Yan
Recently, deep generative models have greatly advanced the progress of face video coding towards promising rate-distortion performance and diverse application functionalities. Beyond traditional hybrid video coding paradigms, Generative Face Video Co
Externí odkaz:
http://arxiv.org/abs/2410.08485
Artificial Intelligence Generated Content (AIGC) is leading a new technical revolution for the acquisition of digital content and impelling the progress of visual compression towards competitive performance gains and diverse functionalities over trad
Externí odkaz:
http://arxiv.org/abs/2402.02140
Generative Face Video Coding (GFVC) techniques can exploit the compact representation of facial priors and the strong inference capability of deep generative models, achieving high-quality face video communication in ultra-low bandwidth scenarios. Th
Externí odkaz:
http://arxiv.org/abs/2311.02649
In this letter, we envision a new metaverse communication paradigm for virtual avatar faces, and develop the semantic face compression with compact 3D facial descriptors. The fundamental principle is that the communication of virtual avatar faces pri
Externí odkaz:
http://arxiv.org/abs/2311.12817
Recent years have witnessed an exponential increase in the demand for face video compression, and the success of artificial intelligence has expanded the boundaries beyond traditional hybrid video coding. Generative coding approaches have been identi
Externí odkaz:
http://arxiv.org/abs/2304.07056
In this paper, we propose a novel framework for Interactive Face Video Coding (IFVC), which allows humans to interact with the intrinsic visual representations instead of the signals. The proposed solution enjoys several distinct advantages, includin
Externí odkaz:
http://arxiv.org/abs/2302.09919
Autor:
Han, Yourui1 (AUTHOR), Chen, Bolin1,2 (AUTHOR) blchen@nwpu.edu.cn, Bi, Zhongwen3 (AUTHOR), Bian, Jun4 (AUTHOR) blchen@nwpu.edu.cn, Kang, Ruiming5 (AUTHOR), Shang, Xuequn1,6 (AUTHOR)
Publikováno v:
Briefings in Bioinformatics. Nov2024, Vol. 25 Issue 6, p1-12. 12p.
