no code implementations • 21 Oct 2024 • Shizhen Zhao, Xin Wen, Jiahui Liu, Chuofan Ma, Chunfeng Yuan, Xiaojuan Qi
To prevent the overwhelming presence of auxiliary classes from disrupting training, we introduce a neighbor-silencing loss that encourages the model to focus on class discrimination within the target dataset.
1 code implementation • 8 Sep 2024 • Jiahui Liu, Xin Wen, Shizhen Zhao, Yingxian Chen, Xiaojuan Qi
Out-of-distribution (OOD) object detection is a challenging task due to the absence of open-set OOD data.
1 code implementation • 11 Oct 2022 • Shizhen Zhao, Xiaojuan Qi
Most existing 3D point cloud object detection approaches heavily rely on large amounts of labeled training data.
1 code implementation • ICCV 2021 • Shizhen Zhao, Changxin Gao, Yuanjie Shao, Wei-Shi Zheng, Nong Sang
Specifically, to alleviate the intra-class variations, a clustering method is utilized to generate pseudo labels for both visual and textual instances.
1 code implementation • 11 Sep 2020 • Fufu Yu, Xinyang Jiang, Yifei Gong, Shizhen Zhao, Xiaowei Guo, Wei-Shi Zheng, Feng Zheng, Xing Sun
Secondly, the Conditional Feature Embedding requires the overall feature of a query image to be dynamically adjusted based on the gallery image it matches, while most of the existing methods ignore the reference images.
Ranked #1 on Person Re-Identification on CUHK03-C
1 code implementation • ECCV 2020 • Shizhen Zhao, Changxin Gao, Jun Zhang, Hao Cheng, Chuchu Han, Xinyang Jiang, Xiaowei Guo, Wei-Shi Zheng, Nong Sang, Xing Sun
In the conventional person Re-ID setting, it is widely assumed that cropped person images are for each individual.
1 code implementation • 19 Jan 2020 • Shizhen Zhao, Changxin Gao, Yuanjie Shao, Lerenhan Li, Changqian Yu, Zhong Ji, Nong Sang
FFU and BFU add the IoU variance to the results of CFU, yielding class-specific foreground and background features, respectively.