SeCo: Separating Unknown Musical Visual Sounds with Consistency Guidance

no code implementations • 25 Mar 2022 • Xinchi Zhou, Dongzhan Zhou, Wanli Ouyang, Hang Zhou, Ziwei Liu, Di Hu

Recent years have witnessed the success of deep learning on the visual sound separation task.

Delving into Localization Errors for Monocular 3D Object Detection

1 code implementation • CVPR 2021 • Xinzhu Ma, Yinmin Zhang, Dan Xu, Dongzhan Zhou, Shuai Yi, Haojie Li, Wanli Ouyang

Estimating 3D bounding boxes from monocular images is an essential component in autonomous driving, while accurate 3D object detection from this kind of data is very challenging.

Autonomous Driving Monocular 3D Object Detection +1

Performance Optimization for Federated Person Re-identification via Benchmark Analysis

2 code implementations • 26 Aug 2020 • Weiming Zhuang, Yonggang Wen, Xuesen Zhang, Xin Gan, Daiying Yin, Dongzhan Zhou, Shuai Zhang, Shuai Yi

Then we propose two optimization methods: (1) To address the unbalanced weight problem, we propose a new method to dynamically change the weights according to the scale of model changes in clients in each training round; (2) To facilitate convergence, we adopt knowledge distillation to refine the server model with knowledge generated from client models on a public dataset.

Federated Learning Knowledge Distillation +2

Cheaper Pre-training Lunch: An Efficient Paradigm for Object Detection

no code implementations • ECCV 2020 • Dongzhan Zhou, Xinchi Zhou, Hongwen Zhang, Shuai Yi, Wanli Ouyang

In this paper, we propose a general and efficient pre-training paradigm, Montage pre-training, for object detection.

object-detection Object Detection

EcoNAS: Finding Proxies for Economical Neural Architecture Search

no code implementations • CVPR 2020 • Dongzhan Zhou, Xinchi Zhou, Wenwei Zhang, Chen Change Loy, Shuai Yi, Xuesen Zhang, Wanli Ouyang

While many methods have been proposed to improve the efficiency of NAS, the search progress is still laborious because training and evaluating plausible architectures over large search space is time-consuming.

Neural Architecture Search

WIDER Face and Pedestrian Challenge 2018: Methods and Results

no code implementations • 19 Feb 2019 • Chen Change Loy, Dahua Lin, Wanli Ouyang, Yuanjun Xiong, Shuo Yang, Qingqiu Huang, Dongzhan Zhou, Wei Xia, Quanquan Li, Ping Luo, Junjie Yan, Jian-Feng Wang, Zuoxin Li, Ye Yuan, Boxun Li, Shuai Shao, Gang Yu, Fangyun Wei, Xiang Ming, Dong Chen, Shifeng Zhang, Cheng Chi, Zhen Lei, Stan Z. Li, Hongkai Zhang, Bingpeng Ma, Hong Chang, Shiguang Shan, Xilin Chen, Wu Liu, Boyan Zhou, Huaxiong Li, Peng Cheng, Tao Mei, Artem Kukharenko, Artem Vasenin, Nikolay Sergievskiy, Hua Yang, Liangqi Li, Qiling Xu, Yuan Hong, Lin Chen, Mingjun Sun, Yirong Mao, Shiying Luo, Yongjun Li, Ruiping Wang, Qiaokang Xie, Ziyang Wu, Lei Lu, Yiheng Liu, Wengang Zhou

This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian.

Face Detection Pedestrian Detection +1