About Me

I am a Research Scientist at King Abdullah University of Science and Technology (KAUST), and Lead of the Video Group in Image and Video Understanding Lab (IVUL) with Prof. Bernard Ghanum. I obtained my Ph.D from Peking University (PKU), advised by Prof. Wen Gao and Prof. Siwei Ma. My research interests focus on image/video understanding (after I got my Ph.D) and image/video compression (during my Ph.D study).

I have published 40+ papers in representative journals and conferences in both fields, such as TPAMI, CVPR, ICCV, ECCV in the field of image/video understanding, and TCSVT, TIP, DCC in the field of image/video compression. I received the Best Paper Nomination in CVPR 2022, the Best Paper Award in CVPR workshop 2023, and the Best Paper Award in NCMT 2015. I have also be awarded the First Prize of Qualcomm Innovation Fellowship Contest (QInF) (only 2 in China), and Goldman Sachs Global Leaders Award (only 26 in the mainland China and 150 worldwide).

Interests
  • Image/video understanding
  • Vision-languange learning
  • Efficient neural networks
  • Image/video processing
  • Image/video compression
  • Image/video continual learning
Education

  • Ph.D. in Computer Science, 2016

    Peking University (PKU), Beijing, China

  • Research Intern, 2016

    National Institute of Informatics (NII), Tokyo, Japan

  • Joint Ph.D. student, 2012

    University of Washington (UW), Seattle, USA

  • B.Eng. in Software Engineering, 2010

    Sichuan University (SCU), Chengdu, China

News

2024

2023

  • [2023-08-08] EgoLoc is selected as an ORAL in ICCV'23!
  • [2023-08-07] Ego4D（extended from our CVPR'22 paper）was accepted to TPAMI!
  • [2023-07-14] All three papers (LAE, FreeDoM, EgoLoc) submitted to ICCV'23 were accepted!
  • [2023-06-22] SMILE won the Best Paper Award in CVPRW'23 CLVision!
  • [2023-06-22] We won the first place in CVPR'23 Ego4D VQ3D Challenge!
  • [2023-04-07] ETAD was accepted to CVPRW'23 ECV!
  • [2023-04-04] OWL was accepted to CVPRW'23 L3D-IVU !
  • [2023-03-29] SMILE was accepted to CVPRW'23 CLVision!
  • [2023-02-27] Re2TAL and LF-VSN were accepted to CVPR'23!
  • [2023-02-20] I gave a spotlight talk in the Rising Star in AI Symposium !

2022

  • [2022-12-02] I was the lecturer in the Artificial Intelligence Bootcamp on behalf of KAUST to Saudi Arabia’s smartest undergraduate students!
  • [2022-07-04] R-DFCIL and EASEE were accepted into ECCV'22!
  • [2022-06-21] Ego4D got into CVPR'22 Best Paper Finalist!
  • [2022-04-18] All Ego4D challenges are live now!
  • [2022-03-29] Ego4D was accepted to CVPR'22 as ORAL presentation!
  • [2022-03-29] MAD was accepted to CVPR'22!

2021

  • [2021-10-15] Ego4D was released and paper on arxiv!
  • [2021-07-23] VSGN was accepted to ICCV'21!
  • [2021-05-20] I was recognized by CVPR’21 as Outstanding Reviewer!

2020

  • [2020-07-29] ThumbNet was accepted to ACM MM'20!
  • [2020-06-07] We won the 2‑nd place in the HACS’20 Weakly‑supervised action detection Challenge!
  • [2020-02-27] G-TAD was accepted to CVPR'20!

2019

  • [2019-10-23] Our paper for YouTube-8M challenge got accepted as Oral presentation in ICCV'19 Workshop!
  • [2019-10-12] We missed the gold medal by only 0.0004 in Kaggle’s 3rd YouTube‑8M Video Understanding Challenge; rank 9/11 out of 283 teams in the public/private leaderboards!

Publications

Dr2Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient Finetuning
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
Chen Zhao, Shuming Liu, Karttikeya Mangalam, Guocheng Qian, Fatimah Zohra, Abdulmohsen Alghannam, Jitendra Malik, Bernard Ghanem
Large pretrained models are increasingly crucial in modern computer vision tasks. These models are …
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Dr2Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient Finetuning
Re2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
Chen Zhao, Shuming Liu, Karttikeya Mangalam, Bernard Ghanem
Temporal action localization (TAL) requires long-form reasoning to predict actions of various …
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Re2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization
EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
International Conference on Computer Vision (ICCV), 2023. [Won the first place in Ego4D VQ3D Challenge 2023, Oral].
Jinjie Mai, Abdullah Hamdi, Silvio Giancola, Chen Zhao, Bernard Ghanem
With the recent advances in video and 3D understanding, novel 4D spatio-temporal methods fusing both …
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EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
A Unified Continual Learning Framework with General Parameter-Efficient Tuning
International Conference on Computer Vision (ICCV), 2023.
Qiankun Gao, Chen Zhao, Yifan Sun, Teng Xi, Gang Zhang, Bernard Ghanem, Jian Zhang
The ‘pre-training → downstream adaptation’ presents both new opportunities and …
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A Unified Continual Learning Framework with General Parameter-Efficient Tuning
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning
IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2023. [Best Paper Award, Oral].
Lama Alssum, Juan Leo ́n Alca ́zar, Merey Ramazanova, Chen Zhao, Bernard Ghanem
Class-incremental learning is one of the most important settings for the study of Continual …
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Just a Glimpse: Rethinking Temporal Information for Video Continual Learning
Ego4D: Around the World in 3,000 Hours of Egocentric Video
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [Best Paper Nominee, Oral].
Chen Zhao, with other 84 authors
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 …
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Ego4D: Around the World in 3,000 Hours of Egocentric Video
SegTAD: Precise Temporal Action Detection via Semantic Segmentation
European Conference on Computer Vision Workshop (ECCVW), 2022.
Chen Zhao, Merey Ramazanova, Mengmeng Xu, Bernard Ghanem
Temporal action detection (TAD) is an important yet challenging task in video analysis. Most …
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SegTAD: Precise Temporal Action Detection via Semantic Segmentation
Video Self‑Stitching Graph Network for Temporal Action Localization
IEEE International Conference on Computer Vision (ICCV), 2021.
Chen Zhao, Ali Thabet, Bernard Ghanem
Short actions are critical and challenging in the task of action localization. We target this problem and propose a video self-stitching graph network (VSGN), which enhances short action by video self-stitching (VSS) and a cross-scale graph pyramid network (xGPN).
PDF Cite Code Video
Video Self‑Stitching Graph Network for Temporal Action Localization
See all publications

Selected Awards

  • 2023 Best Paper Award, CVPR workshop CLVision
  • 2023 First place, Visual Queries 3D Localization Challenge in Ego4D Workshop at CVPR
  • 2022 First place, Visual Queries 3D Localization Challenge in Ego4D Workshop at ECCV
  • 2021 Outstanding Reviewer, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2020 Finalist, MIT Enterprise Forum Saudi Startup Competition
  • 2020 Second place, HACS Temporal Action Localization Challenge
  • 2019 Finalist, Taqadam Startup Accelerator, Saudi Arabia
  • 2016 Outstanding Graduate, Peking University
  • 2016 Scholarship of Outstanding Talent, Peking University
  • 2015 Best Paper Award, National Conference on Multimedia Technology (NCMT)
  • 2012 First Prize of Qualcomm Innovation Fellowship Contest (QInF), only 2 in China
  • 2012 Outstanding Individual in the Summer Social Practice, Peking University
  • 2010 Outstanding Graduate Leader, Sichuan University
  • 2008 Goldman Sachs Global Leaders Award (only 26 in the China mainland and 150 worldwide)
  • 2007 National Scholarship (Top 1 out of 329 students), Sichuan University
  • 2007 First‑Class Scholarship (Top 1 out of 329 students), Sichuan University

Contact

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