73 citations · 241 across the 38 of their papers we have counts for
7 papers · 1 filter
Disjoint Contrastive Regression Learning for Multi-Sourced Annotations
Xiaoqian Ruan, Gaoang Wang
Large-scale datasets are important for the development of deep learning models. Such datasets usually require a heavy workload of annotations, which are extremely time-consuming an…
ActiveMatch: End-to-end Semi-supervised Active Representation Learning
Xinkai Yuan, Zilinghan Li, Gaoang Wang
Semi-supervised learning (SSL) is an efficient framework that can train models with both labeled and unlabeled data, but may generate ambiguous and non-distinguishable representati…
Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking
Gaoang Wang, Renshu Gu, Zuozhu Liu +3
Vehicle tracking is an essential task in the multi-object tracking (MOT) field. A distinct characteristic in vehicle tracking is that the trajectories of vehicles are fairly smooth…
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…
When Few-Shot Learning Meets Video Object Detection
Zhongjie Yu, Gaoang Wang, Lin Chen +2
Different from static images, videos contain additional temporal and spatial information for better object detection. However, it is costly to obtain a large number of videos with…
DAIL: Dataset-Aware and Invariant Learning for Face Recognition
Gaoang Wang, Lin Chen, Tianqiang Liu +2
To achieve good performance in face recognition, a large scale training dataset is usually required. A simple yet effective way to improve recognition performance is to use a datas…