52 citations · 78 across the 5 of their papers we have counts for
5 papers · 1 filter
Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks
Zhiyuan Cheng, Cheng Han, James Liang +3
Monocular Depth Estimation (MDE) plays a vital role in applications such as autonomous driving. However, various attacks target MDE models, with physical attacks posing significant…
CML-MOTS: Collaborative Multi-task Learning for Multi-Object Tracking and Segmentation
Yiming Cui, Cheng Han, Dongfang Liu
The advancement of computer vision has pushed visual analysis tasks from still images to the video domain. In recent years, video instance segmentation, which aims to track and seg…
E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Cheng Han, Qifan Wang, Yiming Cui +4
As the size of transformer-based models continues to grow, fine-tuning these large-scale pretrained vision models for new tasks has become increasingly parameter-intensive. Paramet…
Human Semantic Segmentation using Millimeter-Wave Radar Sparse Point Clouds
Pengfei Song, Luoyu Mei, Han Cheng
This paper presents a framework for semantic segmentation on sparse sequential point clouds of millimeter-wave radar. Compared with cameras and lidars, millimeter-wave radars have…
YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception
Cheng Han, Qichao Zhao, Shuyi Zhang +3
Over the last decade, multi-tasking learning approaches have achieved promising results in solving panoptic driving perception problems, providing both high-precision and high-effi…