no code implementations • 7 Nov 2023 • Xingzhe He, Zhiwen Cao, Nicholas Kolkin, Lantao Yu, Kun Wan, Helge Rhodin, Ratheesh Kalarot
This strategy enables the model to preserve fine details of the desired subjects, such as text and logos.
1 code implementation • ICCV 2023 • Cheng Han, Qifan Wang, Yiming Cui, Zhiwen Cao, Wenguan Wang, Siyuan Qi, Dongfang Liu
Specifically, we introduce a set of learnable key-value prompts and visual prompts into self-attention and input layers, respectively, to improve the effectiveness of model fine-tuning.
no code implementations • 19 Aug 2022 • Zhiwen Cao, Dongfang Liu, Qifan Wang, Yingjie Chen
In this paper, we propose an Anisotropic Spherical Gaussian (ASG)-based LDL approach for facial pose estimation.
1 code implementation • 11 Jul 2022 • Zhiyuan Cheng, James Liang, Hongjun Choi, Guanhong Tao, Zhiwen Cao, Dongfang Liu, Xiangyu Zhang
Experimental results show that our method can generate stealthy, effective, and robust adversarial patches for different target objects and models and achieves more than 6 meters mean depth estimation error and 93% attack success rate (ASR) in object detection with a patch of 1/9 of the vehicle's rear area.
no code implementations • 15 Oct 2021 • Yiming Cui, Zhiwen Cao, Yixin Xie, Xingyu Jiang, Feng Tao, Yingjie Chen, Lin Li, Dongfang Liu
The existing MOTS studies face two critical challenges: 1) the published datasets inadequately capture the real-world complexity for network training to address various driving settings; 2) the working pipeline annotation tool is under-studied in the literature to improve the quality of MOTS learning examples.
1 code implementation • ICCV 2021 • Yiming Cui, Liqi Yan, Zhiwen Cao, Dongfang Liu
One of the popular solutions is to exploit the temporal information and enhance per-frame representation through aggregating features from neighboring frames.
no code implementations • 14 Oct 2020 • Zhiwen Cao, Zongcheng Chu, Dongfang Liu, Yingjie Chen
This paper proposes to use the three vectors in a rotation matrix as the representation in head pose estimation and develops a new neural network based on the characteristic of such representation.