Ailing Zeng 曾爱玲

Ph.D. Department of Computer Science and Engineering The Chinese University of Hong Kong Visiting Scholar Robotics Institute, Carnegie Mellon University Google Scholar Resume

Biography

I am a researcher of Computer Vision and Robotics at International Digital Economy Academy (IDEA). Previously, I obtained my Ph.D. degree from the department of computer science and engineering, the Chinese University of Hong Kong, supervised by Prof. Qiang Xu. I was a visiting scholar in the Robotics Institute, Carnegie Mellon University. I have also spent wonderful time at Baidu, Microsoft Asia, and Sensetime as a research intern. Before that I got my bachelor’s degrees (Top 1% graduates) of Electronic Engineering and Finance mathematics in Xiamen University.

My research interests include:

1) human-centric visual understanding and perception, like 3d human pose estimation/reconstruction/animation, and human neural rendering;

I'm looking for self-motivated interns at International Digital Economy Academy (IDEA). If you are interested in above topics, please send me your resume by email.

News

• [2023.02] Three papers are accepted to CVPR 2023!

• [2023.01] ED-Pose has been accepted to ICLR 2023.

• [2022.11] LTSF-Linear has been accepted to AAAI 2023 Oral with three strong accept!

• [2022.09] SCINet has been accepted to NeurIPS 2022!

• [2022.09] Check out our recent paper on ViT Feature Knowledge Distillation.

• [2022.07] Invited Talk at OpenMMlab about Human Motion Modeling from a Time Series Perspective. [Slides] [Video]

• [2022.07] Three papers have been accepted to ECCV 2022! (1 oral and 2 posters)

• [2022.01] T-WaveNet has been accepted to ICLR 2022!

• [2021.07] Two papers are accepted to ICCV 2021! (1 oral and 1 poster)

• [2021.05] One paper are accepted to IJCAI 2021!

• [2020.07] One paper are accepted to ECCV 2020!

Publications

One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer [Code] [Homepage] Rank Top-1 for monocular 3D whole-body mesh recovery on AGORA leaderboard! [link] Jing Lin, Ailing Zeng#, Haoqian Wang, Lei Zhang, Yu Li The Thirty-Fourth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 The first one-stage framework for 3D whole-body mesh recovery and an large-scale upper-body dataset.

Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes [Code] [Homepage] Xuan Ju, Ailing Zeng#, Jianan Wang, Qiang Xu, Lei Zhang The Thirty-Fourth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Human-Art contains 50k high-quality images with over 123k person instances from 5 natural and 15 artificial scenarios, which are annotated with bounding boxes, keypoints, self-contact points, and text information for humans represented in both 2D and 3D.

Lite DETR: An Interleaved Multi-Scale Encoder for Efficient DETR [Code] Feng Li, Ailing Zeng, Shilong Liu, Hao Zhang, Hongyang Li, Lionel Ni, Lei Zhang The Thirty-Fourth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 A simple, effective, and general design for lightweight DETR models.

Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation [Code] Jie Yang, Ailing Zeng#, Shilong Liu, Feng Li, Ruimao Zhang#, Lei Zhang Eleventh International Conference on Learning Representations (ICLR), 2023 We present a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation.

Are Transformers Effective for Time Series Forecasting? [Code] [知乎] Ailing Zeng, Muxi Chen, Lei Zhang, Qiang Xu (Oral) Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 We try to question the validity of Transformer-based time series forecasting solutions via a linear layer.

DeciWatch: A Simple Baseline for 10× Efficient 2D and 3D Pose Estimation [Website] [Code] [Data] Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, Qiang Xu European Conference on Computer Vision (ECCV), 2022 DeciWatch is a simple baseline framework with the sample-denoise-recover scheme for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation.

SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos [Website] [Code] [知乎] Ailing Zeng, Lei Yang, Xuan Ju, Jiefeng Li, Jianyi Wang, Qiang Xu European Conference on Computer Vision (ECCV), 2022 SmoothNet is a refinement network, which can be attached to any existing pose estimators to improve their temporal smoothness and enhance the per-frame precision.

HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling [Website] Zhongang Cai*, Daxuan Ren*, Ailing Zeng*, Zhengyu Lin*, Tao Yu*, Wenjia Wang*, Xiangyu Fan, Yang Gao, Yifan Yu, Liang Pan, Fangzhou Hong, Mingyuan Zhang, Chen Change Loy, Lei Yang^, Ziwei Liu^ (Oral) European Conference on Computer Vision (ECCV), 2022 HuMMan is a large-scale multi-modal 4D human dataset with 1000 human subjects, 400k sequences and 60M frames.

SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction [Code] Minhao Liu, Ailing Zeng, Qiuxia Lai, Qiang Xu Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022 We propose a novel and general CNN-based backbone for the time series forecasting problem, achieving SOTAs on several real-world datasets.

T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis [Code] Minhao Liu, Ailing Zeng, Qiuxia Lai, Qiang Xu 2022 Tenth International Conference on Learning Representations (ICLR'22) We introduce a tree-structured wavelet deep neural network to effectively extract more discriminative and expressive feature representations in time series signals.

Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation Ailing Zeng, Xiao Sun, Lei Yang, Nanxuan Zhao, Minhao Liu, Qiang Xu 2021 IEEE/CVF International Conference on Computer Vision (ICCV’21) We explore a novel skeletal graph neural network to deal with hard poses in 3D pose estimation.

Human Pose Regression with Residual Log-likelihood Estimation [Code] [知乎] Jiefeng Li, Siyuan Bian, Ailing Zeng, Can Wang, Bo Pang, Wentao Liu and Cewu Lu (Oral) 2021 IEEE/CVF International Conference on Computer Vision (ICCV’21) We propose a novel regression paradigm, which is superior to the heatmap-based methods for the first time, especially on multi-person pose estimation.

SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approach [Code] Ailing Zeng, Xiao Sun, Fuyang Huang, Minhao Liu, Qiang Xu, Stephen Lin 2020 European Conference on Computer Vision (ECCV’20) We design a split-and-recombine approach to improve generalization performance in 3D human pose estimation, especially on rare and unseen poses.

Working Experience

• Researcher at International Digital Economy Academy. (Apr. 2022 to now)
  Worked on human-centric computer vision.

• Research intern at Sensetime Research. (Nov. 2020 to Apr. 2022)
  Worked on robust and efficient 2D/3D human pose estimation&reconstruction from videos.

• Research intern at Microsoft Asia Research. (Dec. 2019 to Sep. 2020)
  Worked on improving the generalization ability of single-view 3D human pose estimation from either images or videos.

• Research intern at Baidu Research. (June 2018 to Sep. 2018)
  Worked on 2D human pose estimation.

• TMT investment intern at ASB Ventures. (March 2017 to Aug. 2017)
  Analyzed technological feasibility of start-up companies.

• In recent years, I am a reviewer of the following conferences and journals: CVPR, ICCV, ICML, NeurIPS, AAAI, IJCV.

Honors & Awards

• Full Postgraduate Studentship, CUHK (2017 - 2021)

• Excellent League Member, Top 1% student of Xiamen University

• National Scholarship (2015)