Chengjian Feng

I am currently a researcher at Meituan Inc.

Home  /  Email  /  Github  /  Google Scholar


My research interests lie in the areas of computer vision and deep learning. I am particularly interested in object detection, including 2D object detection, 3D object detection (vision-based and LiDAR-based) and open-vocabulary object detection.

clean-usnob AeDet: Azimuth-invariant Multi-view 3D Object Detection
Chenjian Feng, Zequn Jie, Yujie Zhong, Xiangxiang Chu, Lin Ma
CVPR, 2023
project page / arXiv

We propose an Azimuth-equivariant Detector (AeDet) that is able to perform azimuth-invariant multi-view 3D object detection.

clean-usnob PromptDet: Towards Open-vocabulary Detection using Uncurated Images
Chenjian Feng, Yujie Zhong, Zequn Jie, Xiangxiang Chu, Haibing Ren, Xiaolin Wei, Weidi Xie, Lin Ma
ECCV, 2022
project page / arXiv

We propose an open-vocabulary object detector PromptDet, which is able to detect novel categories without any manual annotations.

clean-usnob TOOD: Task-aligned One-stage Object Detection
Chenjian Feng, Yujie Zhong, Yu Gao, Matthew R. Scott, Weilin Huang
ICCV, 2021 (Oral)
project page / arXiv

We propose a Task-aligned One-stage Object Detection (TOOD) that explicitly aligns the classification and localization tasks in a learning-based manner.

clean-usnob Exploring Classification Equilibrium in Long-Tailed Object Detection
Chenjian Feng, Yujie Zhong, Weilin Huang
ICCV, 2021
project page / arXiv

We balance the classification of the long-tailed detector via an Equilibrium Loss (EBL) and a Memory-augmented Feature Sampling (MFS) method.

clean-usnob Domain adaptation with SBADA-GAN and Mean Teacher
Chenjian Feng, Zhaoshui He, Jiawei Wang, Qinzhuang Lin, Zhouping Zhu, Jun Lv, Shengli Xie
Neurocomputing, 2020

We propose a powerful model for unsupervised domain adaptation by introducing Mean Teacher as a target classifier of SBADA-GAN.

Template gratefully stolen from here.