68 citations · 285 across the 36 of their papers we have counts for
7 papers · 1 filter
Semi-DETR: Semi-Supervised Object Detection with Detection Transformers
Jiacheng Zhang, Xiangru Lin, Wei Zhang +6
We analyze the DETR-based framework on semi-supervised object detection (SSOD) and observe that (1) the one-to-one assignment strategy generates incorrect matching when the pseudo…
CityTrack: Improving City-Scale Multi-Camera Multi-Target Tracking by Location-Aware Tracking and Box-Grained Matching
Jincheng Lu, Xipeng Yang, Jin Ye +4
Multi-Camera Multi-Target Tracking (MCMT) is a computer vision technique that involves tracking multiple targets simultaneously across multiple cameras. MCMT in urban traffic visua…
Multi-Modal 3D Object Detection by Box Matching
Zhe Liu, Xiaoqing Ye, Zhikang Zou +5
Multi-modal 3D object detection has received growing attention as the information from different sensors like LiDAR and cameras are complementary. Most fusion methods for 3D detect…
ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box
Yifu Zhang, Xinggang Wang, Xiaoqing Ye +6
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects across video frames. Detection boxes serve as the basis of both 2D and 3D MOT. The inevitabl…
Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection
Chang Liu, Weiming Zhang, Xiangru Lin +6
With basic Semi-Supervised Object Detection (SSOD) techniques, one-stage detectors generally obtain limited promotions compared with two-stage clusters. We experimentally find that…
CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
Kaixin Xiong, Shi Gong, Xiaoqing Ye +5
In this paper, we address the problem of detecting 3D objects from multi-view images. Current query-based methods rely on global 3D position embeddings (PE) to learn the geometric…
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection
Zhe Liu, Xiaoqing Ye, Xiao Tan +2
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors…