25 citations · 80 across the 20 of their papers we have counts for
8 papers · 1 filter
Multiple Object Tracking Challenge Technical Report for Team MT_IoT
Feng Yan, Zhiheng Li, Weixin Luo +4
This is a brief technical report of our proposed method for Multiple-Object Tracking (MOT) Challenge in Complex Environments. In this paper, we treat the MOT task as a two-stage ta…
AeDet: Azimuth-invariant Multi-view 3D Object Detection
Chengjian Feng, Zequn Jie, Yujie Zhong +2
Recent LSS-based multi-view 3D object detection has made tremendous progress, by processing the features in Brid-Eye-View (BEV) via the convolutional detector. However, the typical…
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation
Jinlong Li, Zequn Jie, Xu Wang +2
Generating precise class-aware pseudo ground-truths, a.k.a, class activation maps (CAMs), is essential for weakly-supervised semantic segmentation. The original CAM method usually…
MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection
Yang Jiao, Zequn Jie, Shaoxiang Chen +3
Fusing LiDAR and camera information is essential for achieving accurate and reliable 3D object detection in autonomous driving systems. This is challenging due to the difficulty of…
MT-Net Submission to the Waymo 3D Detection Leaderboard
Shaoxiang Chen, Zequn Jie, Xiaolin Wei +1
In this technical report, we introduce our submission to the Waymo 3D Detection leaderboard. Our network is based on the Centerpoint architecture, but with significant improvements…
PromptDet: Towards Open-vocabulary Detection using Uncurated Images
Chengjian Feng, Yujie Zhong, Zequn Jie +5
The goal of this work is to establish a scalable pipeline for expanding an object detector towards novel/unseen categories, using zero manual annotations. To achieve that, we make…
MORE: Multi-Order RElation Mining for Dense Captioning in 3D Scenes
Yang Jiao, Shaoxiang Chen, Zequn Jie +3
3D dense captioning is a recently-proposed novel task, where point clouds contain more geometric information than the 2D counterpart. However, it is also more challenging due to th…
Suspected Object Matters: Rethinking Model's Prediction for One-stage Visual Grounding
Yang Jiao, Zequn Jie, Jingjing Chen +2
Recently, one-stage visual grounders attract high attention due to their comparable accuracy but significantly higher efficiency than two-stage grounders. However, inter-object rel…