no code implementations • 5 Jun 2024 • Haoran Cheng, Liang Peng, Linxuan Xia, Yuepeng Hu, Hengjia Li, Qinglin Lu, Xiaofei He, Boxi Wu
Specifically, we divide T2V generation process into two steps: (i) For a given prompt input, we search existing text-video datasets to find videos with text labels that closely match the prompt motions.
no code implementations • 2 Feb 2024 • Guanwen Feng, Haoran Cheng, Yunan Li, Zhiyuan Ma, Chaoneng Li, Zhihao Qian, Qiguang Miao, Chi-Man Pun
Additionally, we propose an emotion intensity control method using a fine-grained emotion matrix.
1 code implementation • 19 Dec 2023 • Junkai Xu, Liang Peng, Haoran Cheng, Linxuan Xia, Qi Zhou, Dan Deng, Wei Qian, Wenxiao Wang, Deng Cai
To resolve this problem, we propose to regulate intermediate dense 3D features with the help of volume rendering.
1 code implementation • 29 Nov 2023 • Liang Peng, Haoran Cheng, Zheng Yang, Ruisi Zhao, Linxuan Xia, Chaotian Song, Qinglin Lu, Boxi Wu, Wei Liu
By applying the loss to existing one-shot video tuning methods, we significantly improve the overall consistency and smoothness of the generated videos.
no code implementations • 18 Oct 2023 • Haoran Cheng, Dixin Luo, Hongteng Xu
Given two graphs, we align their node embeddings within the same modality and across different modalities, respectively.
1 code implementation • ICCV 2023 • Junkai Xu, Liang Peng, Haoran Cheng, Hao Li, Wei Qian, Ke Li, Wenxiao Wang, Deng Cai
To the best of our knowledge, this work is the first to introduce volume rendering for M3D, and demonstrates the potential of implicit reconstruction for image-based 3D perception.
1 code implementation • CVPR 2024 • Liang Peng, Junkai Xu, Haoran Cheng, Zheng Yang, Xiaopei Wu, Wei Qian, Wenxiao Wang, Boxi Wu, Deng Cai
Monocular 3D detection is a challenging task due to the lack of accurate 3D information.