activity
20172022
most citedDarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer

21 citations · 50 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CV20226 cited

BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision

Chenyu Yang, Yuntao Chen, Hao Tian +9

We present a novel bird's-eye-view (BEV) detector with perspective supervision, which converges faster and better suits modern image backbones. Existing state-of-the-art BEV detect…

cs.CV20227 cited

4D Unsupervised Object Discovery

Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang

Object discovery is a core task in computer vision. While fast progresses have been made in supervised object detection, its unsupervised counterpart remains largely unexplored. Wi…

cs.CV20201 cited

Unsupervised Object Detection with LiDAR Clues

Hao Tian, Yuntao Chen, Jifeng Dai +2

Despite the importance of unsupervised object detection, to the best of our knowledge, there is no previous work addressing this problem. One main issue, widely known to the commun…

cs.CV2019

Sequence Level Semantics Aggregation for Video Object Detection

Haiping Wu, Yuntao Chen, Naiyan Wang +1

Video objection detection (VID) has been a rising research direction in recent years. A central issue of VID is the appearance degradation of video frames caused by fast motion. Th…

cs.CV2019

Revisiting Feature Alignment for One-stage Object Detection

Yuntao Chen, Chenxia Han, Naiyan Wang +1

Recently, one-stage object detectors gain much attention due to their simplicity in practice. Its fully convolutional nature greatly reduces the difficulty of training and deployme…

cs.CV201915 cited

SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

Yuntao Chen, Chenxia Han, Yanghao Li +4

Object detection and instance recognition play a central role in many AI applications like autonomous driving, video surveillance and medical image analysis. However, training obje…