Bingchen Zhao  

I will be a Ph.D student at the University of Edinburgh this fall, supervised by Dr Oisin Mac Aodha.
I am interested in Concept/Category Discovery, Self-Supervised Learning, and Interpretable AI.
Please feel free to drop me an email if you are interested in what I do.


Contact: zhaobc.gm@gmail.com

News
10/2022 Recognised as a Top Reviewer for NeurIPS 2022!.
07/2022 Two papers accepted by ECCV 2022 with one selected as Oral!.
04/2022 We are organizing a workshop at ECCV 2022, check it out here.
02/2022 Received an offer from the University of Edinburgh that is fully-funded.
I've been dreaming about going to Edinburgh since high-school, it's a dream come true.
09/2021 One paper accepted into NeurIPS 2021!
My first time publishing at top-tier machine learning conferences.
07/2021 One paper accepted into ICCV 2021 as Oral!
This is my first main publication in machine learning.
09/2019 - 05/2022 I am working as a teaching assistant for Prof. Yin Wang's Deep Learning Course at Tongji University.
Publications
Conference Papers
XCon: Learning with Experts for Fine-grained Category Discovery
Yixin Fei, Zhongkai Zhao, Siwei Yang, Bingchen Zhao
arXiv / Slides / Code
BMVC 2022 Oral (34/770=4.4%)
TL;DR: Learning to do category discovery within a fine-grained dataset is challenging, we present a method that learn to do that by partition the dataset into k sub-groups, and show improved performance on several fine-grained datasets.
Self-Supervised Visual Representation Learning with Semantic Grouping
Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, Xiaojuan Qi
arXiv / Website / Code
NeurIPS 2022
TL;DR: Our model can do scene decomposition and representation learning at the same time and shows strong generalization ability pretrained on scene-centric data.
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images
Bingchen Zhao, Shaozuo Yu, Wufei Ma, Mingxin Yu, Shenxiao Mei, Angtian Wang, Ju He, Alan Yuille, Adam Kortylewski.
arXiv / Website / Slides
ECCV 2022 Oral (158/5803=2.7%)
TL;DR: We collected a dataset where we have the control over the individual OOD attribute in the test examples.
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective
Quan Cui*, Bingchen Zhao*, Zhao-Min Chen, Borui Zhao, Renjie Song, Jiajun Liang, Boyan Zhou, Osamu Yoshie.
arXiv / Code / Slides
ECCV 2022
TL;DR: We study the transferability and the discriminability of deep representations and found a trade-off between these two properties.
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation
Bingchen Zhao, Kai Han.
arXiv / Code / Slides
NeurIPS 2021
TL;DR: We extend novel category discovery to discover fine-grained classes by leverging information from image parts.
Improving Contrastive Learning by Visualizing Feature Transformation
Rui Zhu*, Bingchen Zhao*, Jingen Liu, Zhenglong Sun, Chang Wen Chen.
arXiv / Code / Slides
ICCV 2021 Oral (210/6236=3.4%)
TL;DR: We explore the training dynamics of self-supervised contrastive learning, and proposed two simple method for improving the performance of the model.
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
Jie Shao*, Xin Wen*, Bingchen Zhao, Xiangyang Xue.
arXiv / Code / Slides
WACV 2021
TL;DR: Video retrieval methods can be improved by modeling long-range temporal information with transformer and contrastive learning.
Workshop Papers / Preprints
A Simple Parametric Classification Baseline for Generalized Category Discovery
Xin Wen*, Bingchen Zhao*, Xiaojuan Qi
arXiv / Code
Preprint
TL;DR: A simple yet effective baseline for Generalized Category Discovery is proposed based on several observations from our investigation, we were able to surpass previous SOTA by a large margin.
One Venue, Two Conferences: The Separation of Chinese and American Citation Networks
Bingchen Zhao*, Yuling Gu*, Jessica Zosa Forde, Naomi Saphra
arXiv
NeurIPS 2022 AI Cultures Workshop
TL;DR: At NeurIPS, American and Chinese institutions cite papers from each other's regions substantially less than they cite endogamously. We build a citation graph to quantify this divide, compare it to European connectivity, and discuss the causes and consequences of the separation.
Distilling Visual Priors from Self-Supervised Learning
Bingchen Zhao, Xin Wen
arXiv / Code / Slides
ECCV 2020 VIPriors Workshop
TL;DR: Learning a model self-supervisedly and then do self-distillation helps in the data-deficient domain.
Awards
2022 Top-Reviewer for NeurIPS 2022.
2020 First-place in the FGVC7 workshop iWildcam challenge track.
2020 Second-place in the ECCV 2020 VIPrior workshop image classification challenge track.
2020 Best Undergraduate Prize in the NeurIPS 2020 SpaceNet 7 challenge.
2016 Bronze medal in the Asia-Pacific Informatics Olympiad.
2015 First Prize in the National Olympiad in Informatics in Provinces.
Professional Services
  I have been a reviewer for ICLR, NeurIPS, CVPR, ICCV, ECCV, WACV, FGVC, and SIGSPATIAL.