Zobrazeno 1 - 10
of 552
pro vyhledávání: '"LIU, YUXIAO"'
Autor:
Cheang, Chi-Lam, Chen, Guangzeng, Jing, Ya, Kong, Tao, Li, Hang, Li, Yifeng, Liu, Yuxiao, Wu, Hongtao, Xu, Jiafeng, Yang, Yichu, Zhang, Hanbo, Zhu, Minzhao
We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable robot manipulation. GR-2 is first pre-trained on a vast number of Internet videos to capture the dynamics of the world. This large-scale pre-training, involvin
Externí odkaz:
http://arxiv.org/abs/2410.06158
The current clinical diagnosis framework of Alzheimer's disease (AD) involves multiple modalities acquired from multiple diagnosis stages, each with distinct usage and cost. Previous AD diagnosis research has predominantly focused on how to directly
Externí odkaz:
http://arxiv.org/abs/2407.18466
Autor:
Zhang, Yutong, Pan, Yi, Zhong, Tianyang, Dong, Peixin, Xie, Kangni, Liu, Yuxiao, Jiang, Hanqi, Liu, Zhengliang, Zhao, Shijie, Zhang, Tuo, Jiang, Xi, Shen, Dinggang, Liu, Tianming, Zhang, Xin
Medical images and radiology reports are crucial for diagnosing medical conditions, highlighting the importance of quantitative analysis for clinical decision-making. However, the diversity and cross-source heterogeneity of these data challenge the g
Externí odkaz:
http://arxiv.org/abs/2407.05758
Scalable robot learning in the real world is limited by the cost and safety issues of real robots. In addition, rolling out robot trajectories in the real world can be time-consuming and labor-intensive. In this paper, we propose to learn an interact
Externí odkaz:
http://arxiv.org/abs/2406.14540
To adequately utilize the available image evidence in multi-view video-based avatar modeling, we propose TexVocab, a novel avatar representation that constructs a texture vocabulary and associates body poses with texture maps for animation. Given mul
Externí odkaz:
http://arxiv.org/abs/2404.00524
Autor:
Zhao, Zihao, Liu, Yuxiao, Wu, Han, Wang, Mei, Li, Yonghao, Wang, Sheng, Teng, Lin, Liu, Disheng, Cui, Zhiming, Wang, Qian, Shen, Dinggang
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising results across various tasks, attributable to its generalizability and int
Externí odkaz:
http://arxiv.org/abs/2312.07353
Autor:
Zhong, Tianyang, Zhao, Wei, Zhang, Yutong, Pan, Yi, Dong, Peixin, Jiang, Zuowei, Kui, Xiaoyan, Shang, Youlan, Yang, Li, Wei, Yaonai, Yang, Longtao, Chen, Hao, Zhao, Huan, Liu, Yuxiao, Zhu, Ning, Li, Yiwei, Wang, Yisong, Yao, Jiaqi, Wang, Jiaqi, Zeng, Ying, He, Lei, Zheng, Chao, Zhang, Zhixue, Li, Ming, Liu, Zhengliang, Dai, Haixing, Wu, Zihao, Zhang, Lu, Zhang, Shu, Cai, Xiaoyan, Hu, Xintao, Zhao, Shijie, Jiang, Xi, Zhang, Xin, Li, Xiang, Zhu, Dajiang, Guo, Lei, Shen, Dinggang, Han, Junwei, Liu, Tianming, Liu, Jun, Zhang, Tuo
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and diverse radiology reports with cross-source heterogeneity pose a huge g
Externí odkaz:
http://arxiv.org/abs/2310.05242
Autor:
Liu, Zhengliang, Zhong, Tianyang, Li, Yiwei, Zhang, Yutong, Pan, Yi, Zhao, Zihao, Dong, Peixin, Cao, Chao, Liu, Yuxiao, Shu, Peng, Wei, Yaonai, Wu, Zihao, Ma, Chong, Wang, Jiaqi, Wang, Sheng, Zhou, Mengyue, Jiang, Zuowei, Li, Chunlin, Holmes, Jason, Xu, Shaochen, Zhang, Lu, Dai, Haixing, Zhang, Kai, Zhao, Lin, Chen, Yuanhao, Liu, Xu, Wang, Peilong, Yan, Pingkun, Liu, Jun, Ge, Bao, Sun, Lichao, Zhu, Dajiang, Li, Xiang, Liu, Wei, Cai, Xiaoyan, Hu, Xintao, Jiang, Xi, Zhang, Shu, Zhang, Xin, Zhang, Tuo, Zhao, Shijie, Li, Quanzheng, Zhu, Hongtu, Shen, Dinggang, Liu, Tianming
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they have made a significant impact in the medical field. Large language model
Externí odkaz:
http://arxiv.org/abs/2307.13693
Creating pose-driven human avatars is about modeling the mapping from the low-frequency driving pose to high-frequency dynamic human appearances, so an effective pose encoding method that can encode high-fidelity human details is essential to human a
Externí odkaz:
http://arxiv.org/abs/2304.13006