Zobrazeno 1 - 10
of 3 006
pro vyhledávání: '"Ye, Yan"'
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
In recent years, large visual language models (LVLMs) have shown impressive performance and promising generalization capability in multi-modal tasks, thus replacing humans as receivers of visual information in various application scenarios. In this p
Externí odkaz:
http://arxiv.org/abs/2407.17060
Autor:
Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao, Li, Chunyi, Kou, Tengchuan, Sun, Wei, Wu, Haoning, Gao, Yixuan, Cao, Yuqin, Zhang, Zicheng, Wu, Xiele, Timofte, Radu, Peng, Fei, Fu, Huiyuan, Ming, Anlong, Wang, Chuanming, Ma, Huadong, He, Shuai, Dou, Zifei, Chen, Shu, Zhang, Huacong, Xie, Haiyi, Wang, Chengwei, Chen, Baoying, Zeng, Jishen, Yang, Jianquan, Wang, Weigang, Fang, Xi, Lv, Xiaoxin, Yan, Jun, Zhi, Tianwu, Zhang, Yabin, Li, Yaohui, Li, Yang, Xu, Jingwen, Liu, Jianzhao, Liao, Yiting, Li, Junlin, Yu, Zihao, Lu, Yiting, Li, Xin, Motamednia, Hossein, Hosseini-Benvidi, S. Farhad, Guan, Fengbin, Mahmoudi-Aznaveh, Ahmad, Mansouri, Azadeh, Gankhuyag, Ganzorig, Yoon, Kihwan, Xu, Yifang, Fan, Haotian, Kong, Fangyuan, Zhao, Shiling, Dong, Weifeng, Yin, Haibing, Zhu, Li, Wang, Zhiling, Huang, Bingchen, Saha, Avinab, Mishra, Sandeep, Gupta, Shashank, Sureddi, Rajesh, Saha, Oindrila, Celona, Luigi, Bianco, Simone, Napoletano, Paolo, Schettini, Raimondo, Yang, Junfeng, Fu, Jing, Zhang, Wei, Cao, Wenzhi, Liu, Limei, Peng, Han, Yuan, Weijun, Li, Zhan, Cheng, Yihang, Deng, Yifan, Li, Haohui, Qu, Bowen, Li, Yao, Luo, Shuqing, Wang, Shunzhou, Gao, Wei, Lu, Zihao, Conde, Marcos V., Wang, Xinrui, Chen, Zhibo, Liao, Ruling, Ye, Yan, Wang, Qiulin, Li, Bing, Zhou, Zhaokun, Geng, Miao, Chen, Rui, Tao, Xin, Liang, Xiaoyu, Sun, Shangkun, Ma, Xingyuan, Li, Jiaze, Yang, Mengduo, Xu, Haoran, Zhou, Jie, Zhu, Shiding, Yu, Bohan, Chen, Pengfei, Xu, Xinrui, Shen, Jiabin, Duan, Zhichao, Asadi, Erfan, Liu, Jiahe, Yan, Qi, Qu, Youran, Zeng, Xiaohui, Wang, Lele, Liao, Renjie
This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major
Externí odkaz:
http://arxiv.org/abs/2404.16687
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
Autor:
Junyong Ou, Dandan Su, Yunhe Guan, Liyuan Ge, Shaohui Deng, Ye Yan, Yichang Hao, Min Lu, Shudong Zhang, Ruiyang Xie
Publikováno v:
Discover Oncology, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Introduction Desmoid tumors (DT) are rare, locally invasive tumors originating from connective tissue. Surgical intervention is no longer the standard treatment for DT, as systemic therapy gradually replaces it due to its superior efficacy.
Externí odkaz:
https://doaj.org/article/b113be7f390d4f5fbabd5e2595713340
