3k citations · 4.7k across the 43 of their papers we have counts for
43 papers
GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection
Weixin Mao, Jinrong Yang, Zheng Ge +5
Depth perception is a crucial component of monoc-ular 3D detection tasks that typically involve ill-posed problems. In light of the success of sample mining techniques in 2D object…
Dynamic Grained Encoder for Vision Transformers
Lin Song, Songyang Zhang, Songtao Liu +5
Transformers, the de-facto standard for language modeling, have been recently applied for vision tasks. This paper introduces sparse queries for vision transformers to exploit the…
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation
En Yu, Songtao Liu, Zhuoling Li +4
Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domai…
MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
Hongyu Zhou, Zheng Ge, Zeming Li +1
This paper proposes an efficient multi-camera to Bird's-Eye-View (BEV) view transformation method for 3D perception, dubbed MatrixVT. Existing view transformers either suffer from…
BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo
Yinhao Li, Han Bao, Zheng Ge +3
Bounded by the inherent ambiguity of depth perception, contemporary camera-based 3D object detection methods fall into the performance bottleneck. Intuitively, leveraging temporal…
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…