15 citations · 52 across the 13 of their papers we have counts for
8 papers · 1 filter
Towards 3D Object Detection with 2D Supervision
Jinrong Yang, Tiancai Wang, Zheng Ge +3
The great progress of 3D object detectors relies on large-scale data and 3D annotations. The annotation cost for 3D bounding boxes is extremely expensive while the 2D ones are easi…
Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking
Pan Wang, Liangliang Ren, Shengkai Wu +4
The point cloud based 3D single object tracking has drawn increasing attention. Although many breakthroughs have been achieved, we also reveal two severe issues. By extensive analy…
Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking
Jinrong Yang, En Yu, Zeming Li +2
3D Multi-Object Tracking (MOT) has achieved tremendous achievement thanks to the rapid development of 3D object detection and 2D MOT. Recent advanced works generally employ a serie…
StreamYOLO: Real-time Object Detection for Streaming Perception
Jinrong Yang, Songtao Liu, Zeming Li +2
The perceptive models of autonomous driving require fast inference within a low latency for safety. While existing works ignore the inevitable environmental changes after processin…
DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection
Jinrong Yang, Lin Song, Songtao Liu +6
Many point-based 3D detectors adopt point-feature sampling strategies to drop some points for efficient inference. These strategies are typically based on fixed and handcrafted rul…
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics
Lijun Gou, Jinrong Yang, Hangcheng Yu +3
Unsupervised domain adaptation is critical in various computer vision tasks, such as object detection, instance segmentation, etc. They attempt to reduce domain bias-induced perfor…
Real-time Object Detection for Streaming Perception
Jinrong Yang, Songtao Liu, Zeming Li +2
Autonomous driving requires the model to perceive the environment and (re)act within a low latency for safety. While past works ignore the inevitable changes in the environment aft…
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
Zonghang Li, Yihong He, Hongfang Yu +4
Nowadays, the industrial Internet of Things (IIoT) has played an integral role in Industry 4.0 and produced massive amounts of data for industrial intelligence. These data locate o…