227 citations · 389 across the 11 of their papers we have counts for
11 papers
Vision meets mmWave Radar: 3D Object Perception Benchmark for Autonomous Driving
Yizhou Wang, Jen-Hao Cheng, Jui-Te Huang +8
Sensor fusion is crucial for an accurate and robust perception system on autonomous vehicles. Most existing datasets and perception solutions focus on fusing cameras and LiDAR. How…
GaitTAKE: Gait Recognition by Temporal Attention and Keypoint-guided Embedding
Hung-Min Hsu, Yizhou Wang, Cheng-Yen Yang +3
Gait recognition, which refers to the recognition or identification of a person based on their body shape and walking styles, derived from video data captured from a distance, is w…
ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot
Jiarui Cai, Yizhou Wang, Jenq-Neng Hwang
One-stage long-tailed recognition methods improve the overall performance in a "seesaw" manner, i.e., either sacrifice the head's accuracy for better tail classification or elevate…
Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment
Yizhou Wang, Gaoang Wang, Hung-Min Hsu +2
Radar has long been a common sensor on autonomous vehicles for obstacle ranging and speed estimation. However, as a robust sensor to all-weather conditions, radar's capability has…
Split and Connect: A Universal Tracklet Booster for Multi-Object Tracking
Gaoang Wang, Yizhou Wang, Renshu Gu +2
Multi-object tracking (MOT) is an essential task in the computer vision field. With the fast development of deep learning technology in recent years, MOT has achieved great improve…
Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model
Hung-Min Hsu, Jiarui Cai, Yizhou Wang +2
In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT) of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based…
RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization
Yizhou Wang, Zhongyu Jiang, Yudong Li +3
Various autonomous or assisted driving strategies have been facilitated through the accurate and reliable perception of the environment around a vehicle. Among the commonly used se…
Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model
Hung-Min Hsu, Yizhou Wang, Jenq-Neng Hwang
Multi-target multi-camera tracking (MTMCT), i.e., tracking multiple targets across multiple cameras, is a crucial technique for smart city applications. In this paper, we propose a…
IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency
Jiarui Cai, Yizhou Wang, Haotian Zhang +3
Multiple object tracking (MOT) is a crucial task in computer vision society. However, most tracking-by-detection MOT methods, with available detected bounding boxes, cannot effecti…
RODNet: Radar Object Detection Using Cross-Modal Supervision
Yizhou Wang, Zhongyu Jiang, Xiangyu Gao +3
Radar is usually more robust than the camera in severe driving scenarios, e.g., weak/strong lighting and bad weather. However, unlike RGB images captured by a camera, the semantic…
Exploit the Connectivity: Multi-Object Tracking with TrackletNet
Gaoang Wang, Yizhou Wang, Haotian Zhang +2
Multi-object tracking (MOT) is an important and practical task related to both surveillance systems and moving camera applications, such as autonomous driving and robotic vision. H…