no code implementations • 23 Apr 2024 • Jinfan Liu, Yichao Yan, Junjie Li, Weiming Zhao, Pengzhi Chu, Xingdong Sheng, Yunhui Liu, Xiaokang Yang
Video anomaly detection (VAD) is a challenging task aiming to recognize anomalies in video frames, and existing large-scale VAD researches primarily focus on road traffic and human activity scenes.
no code implementations • 19 Apr 2024 • Junjie Li, Guanshuo Wang, Fufu Yu, Yichao Yan, Qiong Jia, Shouhong Ding, Xingdong Sheng, Yunhui Liu, Xiaokang Yang
However, such improvement sacrifices the performance under the standard protocol, caused by the inner conflict between standard and CC.
no code implementations • 26 Dec 2023 • Liang Xu, Xintao Lv, Yichao Yan, Xin Jin, Shuwen Wu, Congsheng Xu, Yifan Liu, Yizhou Zhou, Fengyun Rao, Xingdong Sheng, Yunhui Liu, Wenjun Zeng, Xiaokang Yang
We also equip Inter-X with versatile annotations of more than 34K fine-grained human part-level textual descriptions, semantic interaction categories, interaction order, and the relationship and personality of the subjects.
1 code implementation • 12 Sep 2022 • Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine
In this work, we introduce a framework for training generalized locomotion (GenLoco) controllers for quadrupedal robots.
no code implementations • 3 Aug 2022 • Ziyi Wang, Bo Lu, Yonghao Long, Fangxun Zhong, Tak-Hong Cheung, Qi Dou, Yunhui Liu
In addition, we provide experimental results with state-of-the-art models as reference benchmarks for further model developments and evaluations on this dataset.
1 code implementation • 25 Mar 2022 • Jiaxin Guo, Fangxun Zhong, Rong Xiong, Yunhui Liu, Yue Wang, Yiyi Liao
In this paper, we take a deeper look at the inference of analysis-by-synthesis from the perspective of visual navigation, and investigate what is a good navigation policy for this specific task.
no code implementations • 23 Nov 2021 • Qiang Nie, Ziwei Liu, Yunhui Liu
Inspired by this, we propose a new framework that leverages the labeled 3D human poses to learn a 3D concept of the human body to reduce the ambiguity.
no code implementations • 8 Oct 2021 • Ruofeng Wei, Bin Li, Hangjie Mo, Bo Lu, Yonghao Long, Bohan Yang, Qi Dou, Yunhui Liu, Dong Sun
Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction.