T
Tianheng Cheng
Researcher at Huazhong University of Science and Technology
Publications - 25
Citations - 5015
Tianheng Cheng is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Computer science & Object detection. The author has an hindex of 7, co-authored 10 publications receiving 1950 citations.
Papers
More filters
Posted Content
MMDetection: Open MMLab Detection Toolbox and Benchmark.
Kai Chen,Jiaqi Wang,Jiangmiao Pang,Yuhang Cao,Yu Xiong,Xiaoxiao Li,Shuyang Sun,Wansen Feng,Ziwei Liu,Jiarui Xu,Zheng Zhang,Dazhi Cheng,Chenchen Zhu,Tianheng Cheng,Qijie Zhao,Buyu Li,Xin Lu,Rui Zhu,Yue Wu,Jifeng Dai,Jingdong Wang,Jianping Shi,Wanli Ouyang,Chen Change Loy,Dahua Lin +24 more
TL;DR: This paper presents MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules, and conducts a benchmarking study on different methods, components, and their hyper-parameters.
Posted Content
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang,Ke Sun,Tianheng Cheng,Borui Jiang,Chaorui Deng,Yang Zhao,Dong Liu,Yadong Mu,Mingkui Tan,Xinggang Wang,Wenyu Liu,Bin Xiao +11 more
TL;DR: The superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, is shown, suggesting that the HRNet is a stronger backbone for computer vision problems.
Journal ArticleDOI
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang,Ke Sun,Tianheng Cheng,Borui Jiang,Chaorui Deng,Yang Zhao,Dong Liu,Yadong Mu,Mingkui Tan,Xinggang Wang,Wenyu Liu,Bin Xiao +11 more
TL;DR: The High-Resolution Network (HRNet) as mentioned in this paper maintains high-resolution representations through the whole process by connecting the high-to-low resolution convolution streams in parallel and repeatedly exchanging the information across resolutions.
Posted Content
High-Resolution Representations for Labeling Pixels and Regions
Ke Sun,Yang Zhao,Borui Jiang,Tianheng Cheng,Bin Xiao,Dong Liu,Yadong Mu,Xinggang Wang,Wenyu Liu,Jingdong Wang +9 more
TL;DR: A simple modification is introduced to augment the high-resolution representation by aggregating the (upsampled) representations from all the parallel convolutions rather than only the representation from thehigh-resolution convolution, which leads to stronger representations, evidenced by superior results.
Proceedings ArticleDOI
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning
Ji Zhang,Yu Liu,Ke Zhou,Guoliang Li,Zhili Xiao,Bin Cheng,Jiashu Xing,Yangtao Wang,Tianheng Cheng,Li Liu,Minwei Ran,Zekang Li +11 more
TL;DR: An end-to-end automatic CDB tuning system, CDBTune, using deep reinforcement learning (RL), which enables end- to-end learning and accelerates the convergence speed of the model and improves efficiency of online tuning.