Bin-Bin Gao's homepage

Biography

I am a Senior Researcher at Tencent YouTu Lab in Shenzhen. Previously, I received my Ph.D. in Nanjing University at LAMDA Group, led by Prof. Zhi-Hua Zhou (foreign member of the Academy of Europe, ACM/AAAI/AAAS/IEEE/IAPR Fellow), advised by Prof. Jianxin Wu (member of the Thousand Talents Plan). Before that, I got my B.S. degree in applied mathematics in 2010, and received my M.S. degree in 2013 from Southwest University, Chongqing China. My research interests include computer vision and machine learning, especially visual recognition and deep learning. I have severed as a reviewer (or PC member) for CVPR, ICCV, NeurIPS, AAAI, ECCV, ACCV, WACV, TIP, TKDE, TMI, TII, TNNLS, NN, Neurocomputing etc.

Research

General Object Recognition

Multi-Label Image Recognition [TIP 21]
Change Detection [PR 22]
Open-Vocabulary Object Detection

Few-Shot Learning

Image Classification [IJCAI 23]
Semantic Segmentation [TMM 22]
Object Detection and Instance Segmentation [NeurIPS 22]

Continual Learning

Image Classification [TMM 23]
Object Detection [AAAI 24]

Anomaly Detection

Unified Anomaly Detection
Universal Anomaly Detection
Fully Unsupervised Anomaly Detection [CVPR 24]

Earlier Works

Deep Label Distribution Leaning [TIP 17] [IJCAI 18]
Visual (Image and Video) Representation [AAAI 16]
Support Vector Machine [ICMLA 15]

csgaobb at gmail dot com

I am recruiting self-motivated interns in computer vision. If you are interested in, please directly send your CV to my email danylgao at tencent dot com, [招聘JD].

News

Mar. 27, 2024: 🎉🎉🎉 I will be serving as an Area Chair for NeurIPS 2024. It’s an honor to take on this role, and I’m looking forward to contributing to this conference.
Feb. 27, 2024: 🎉🎉🎉 A paper on fully unsupervised anomaly detection benchmark is accepted by CVPR 2024.
Dec. 09, 2023: 🎉🎉🎉 Three papers on anomaly detection, continual detection and matched detection are accepted by AAAI 2024.
Nov. 23, 2023: A paper on cross-modal continual learning is accepted by IEEE Trans. Multimedia.
Mar. 28, 2023: A paper on label distribution learning is accepted by Neural Computing and Applications.
Feb. 24, 2023: A paper on few-shot image classification is accepted by IJCAI-2023.
Jan. 01, 2023: A paper on change detection is accepted by Pattern Recognition.
Nov. 18, 2022: A paper on few-shot image classification is accepted by AAAI 2023.
Sep. 15, 2022: A paper on few-shot object detection and instance segmentation is accepted by NeurIPS 2022.
Jul. 3, 2022: A paper on few-shot image classification is accepted by ECCV 2022.
Jun. 30, 2022: Three papers on continual abnormal detection, few-shot and multi-label image classification are accepted by ACM MM 2022.
May. 06, 2022: A journal paper on few-shot semantic segmentation is accepted by IEEE Trans. Multimedia.
Jun. 05, 2021: A journal paper on multi-label image recognition is accepted by IEEE Trans. Image Processing.
Jul. 26, 2018, I joined Tencent and became a researcher of YouTu X-Lab.
Jun. 21, 2018, I got my Ph.D. in Nanjing University at LAMDA GROUP, advised by Prof. Jianxin Wu.
May 21, 2018, I defended my Ph.D. thesis.
Apr. 17, 2018: A paper is accepted by IJCAI 2018 (Acceptance Rates: 710/3470=20.46%).
Mar. 28, 2018: A paper (in Chinese) is accepted by SCIENTIA SINICA Informatics.
Jul. 31, 2017: A paper accepted to ICCV 2017.
Mar. 26, 2017: A journal paper on deep label distribution learning is accepted by IEEE Trans. Image Processing.
Dec. 11-17, 2015: Attended ICCV 2015.
Nov. 13, 2015: A paper accepted for AAAI 2016.
Oct. 10, 2015: Two papers accepted for ICCV 2015 Workshop.
Sep. 20, 2015: First runner-up in Cultural Event Recognition at ICCV 2015. (with X.-S Wei and J. Wu)

Selected Publications

[Full Publications] [Google Scholar]

Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection
H. Zhang*, B.-B. Gao*, Y. Zeng, X. Tian, X. Tan#, Z. Zhang, Y. Qu, J. Liu and Y. Xie
AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024, pp.7096-7104.
[Code] [CCF-A]

Cross-Modal Alternating Learning with Task-Aware Representations for Continual Learning
W. Li*, B.-B. Gao*#, B. Xia, J. Wang, J. Liu, Y. Liu, C. Wang and F. Zheng
IEEE Transactions on Multimedia (IEEE TMM), 2023, in press.
[Code] [CCF-B, SCI-1, IF:7.3]

How to Reduce Change Detection to Semantic Segmentation
G.-H. Wang, B.-B. Gao# and C. Wang
Pattern Recognition (PR), 2023.
[Code] [CCF-B, SCI-1, IF:8.0]

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation
B.-B. Gao#, X. Chen, Z. Huang, C. Nie, J. Liu, J. Lai, G. Jiang, X. Wang and C. Wang#
Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2022, pp.18640-18652.
[Code] [Project] [Slides] [FSOD-Leaderboard] [CCF-A]

APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation
J. Chen*, B.-B. Gao*#, Z. Lu, J.-H. Xue, C. Wang and Q. Liao
IEEE Transactions on Multimedia (IEEE TMM), 25:4361-4373, 2022.
[Code] [CCF-B, SCI-1, IF:7.3]

Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition
B.-B. Gao# and H.-Y. Zhou
IEEE Transactions on Image Processing (IEEE TIP), 20:5920-5932, 2021.
[Code] [CCF-A, SCI-1, IF:10.6]

Age Estimation Using Expectation of Label Distribution Learning
B.-B. Gao, H.-Y. Zhou, J. Wu# and X. Geng
Int'l Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 2018, pp.712-718.
[Code] [Project] [CCF-A]

Deep Label Distribution Learning with Label Ambiguity
B.-B. Gao, C. Xing, C.-W. Xie, J. Wu# and X. Geng
IEEE Transactions on Image Processing (IEEE TIP), 26(6):2825-2838, 2017.
[Code] [Project] [CCF-A, SCI-1, IF:10.6]

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