no code implementations • 23 Jan 2024 • Hengjia Li, Yang Liu, Yuqi Lin, Zhanwei Zhang, Yibo Zhao, weihang Pan, Tu Zheng, Zheng Yang, Yuchun Jiang, Boxi Wu, Deng Cai
In this paper, we propose UniHDA, a \textbf{unified} and \textbf{versatile} framework for generative hybrid domain adaptation with multi-modal references from multiple domains.
1 code implementation • 30 Oct 2023 • Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Tu Zheng, Zheng Yang, Wenxiao Wang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He
Concretely, the distance loss blends the attributes of all target domains by reducing the distances from generated images to all target subspaces.
1 code implementation • 1 Aug 2023 • Zhihao Chi, Tu Zheng, Hengjia Li, Zheng Yang, Boxi Wu, Binbin Lin, Deng Cai
In this paper, we restudy the hyper-parameter temperature and figure out its incapability to distill the knowledge from each sample sufficiently when it is a single value.
no code implementations • 31 Mar 2023 • Hengjia Li, Tu Zheng, Zhihao Chi, Zheng Yang, Wenxiao Wang, Boxi Wu, Binbin Lin, Deng Cai
To tackle these problems, we propose Asymmetric Parallel Point Transformer (APPT).
3 code implementations • CVPR 2022 • Tu Zheng, Yifei HUANG, Yang Liu, Wenjian Tang, Zheng Yang, Deng Cai, Xiaofei He
In this way, we can exploit more contextual information to detect lanes while leveraging local detailed lane features to improve localization accuracy.
Ranked #1 on Lane Detection on LLAMAS
1 code implementation • CVPR 2022 • Yang Liu, Weifeng Zhang, Chao Xiang, Tu Zheng, Deng Cai, Xiaofei He
Few-shot learning (FSL) aims to learn a classifier that can be easily adapted to accommodate new tasks not seen during training, given only a few examples.
1 code implementation • 1 Apr 2021 • Tu Zheng, Shuai Zhao, Yang Liu, Zili Liu, Deng Cai
In this paper, we propose Side Overlap~(SO) loss by maximizing the side overlap of two bounding boxes, which puts more penalty for low overlapping bounding box cases.
no code implementations • 15 Mar 2021 • Yang Liu, Tu Zheng, Jie Song, Deng Cai, Xiaofei He
In this paper, we argue that a Mutual Nearest Neighbor (MNN) relation should be established to explicitly select the query descriptors that are most relevant to each task and discard less relevant ones from aggregative clutters in FSL.
3 code implementations • 31 Aug 2020 • Tu Zheng, Hao Fang, Yi Zhang, Wenjian Tang, Zheng Yang, Haifeng Liu, Deng Cai
Lane detection is one of the most important tasks in self-driving.
Ranked #4 on Lane Detection on TuSimple
6 code implementations • 2 Sep 2019 • Zili Liu, Tu Zheng, Guodong Xu, Zheng Yang, Haifeng Liu, Deng Cai
Experiments on MS COCO show that our TTFNet has great advantages in balancing training time, inference speed, and accuracy.