Shiming Chen 陈使明

Postdoctoral Research Fellow

Email: gchenshiming at gmail dot com

Short Bios

I received my Ph.D. degree at Huazhong University of Science and Technology in Dec. 2022, advised by Prof. Xinge You and worked closely Prof. Ling Shao. My current research interests span computer vision and machine learning with a series of topics, such as zero-shot learning, generative modeling and learning, and visual-and-language learning.

News

2024.02, Our TWO paper on zero-shot learning are accepted to CVPR'24.
2024.02, Our SURVEY on few-shot object detection is accepted to Information Fusion, congrating to Zhimeng.
2024.01, Our paper on Non-Transferable Representation Learning is accepted to ICLR'24 (Spotlight), congrating to Ziming.
2023.12, Our paper on zero-shot learning is accepted to Science China Information Sciences, congrating to Shuhuang.
2023.11, I give a talk in Harbin Institute of Technology (Shenzhen), invited by Prof. Haijun Zhang.
2023.10, I organize a VALSE Webinar on "Zero-shot Learning in Vision". Thanks for the exciting sharing of Prof. Jingjing Li, Prof. Kaiyang Zhou, Dr. Yongqin Xian, and Prof. Zhong Ji.
2023.09, I give a talk in ZHEJIANG LAB, invited by Dr. Jin Zhao.
2023.08, one paper on zero-shot learning is accepted to TEC.
2023.07, Our paper on rainy image generation is accepted to ICCV'23.
2023.07, I am invited as an Area Chair (AC) of PRCV'23.
2023.06, I give a talk in University of Science and Technology of China, invited by Prof. Hongtao Xie.
2023.04, Our paper on zero-shot learning is accepted to ICML'23.
2023.04, I give a talk in Alibaba DAMO Academic, invited by Baigui Sun.
2023.04, I give a talk in Huazhong Agricultural Univeristy, invited by Prof. Hong Chen.
2023.04, I give a talk in Guizhou University, invited by Prof. Yisong Wang.
2023.03, I am invited as an Area Chair (AC) of VALSE, news at Here.
2023.03, I give a talk in National Key Laboratory of Science and Technology on Multispectral Information Processing, invited by Prof. Yi Chang.
2022.12, Our TransZero++ is accepted to TPAMI.
2022.08, I was invited as a Program Committee (PC) Member for AAAI'23.
2022.05, I give a talk about our CVPR'22 work (MSDN) in VALSE.
2022.05, I give a talk about zero-shot learning in AI TIME and AI Drive.
2022.04, Our paper on zero-shot learning is accepted to IJCAI'22.
2022.04, We have released the full codes of TransZero accepted to AAAI'22.
2022.03, Our paper on zero-shot learning is accepted to CVPR'22.
2022.02, I gave a talk in Extreme Mart (极市).
2022.02, Our paper on zero-shot learning is accepted to TNNLS.
2022.02, I gave a talk in AI TIME PhD-NeurIPS, invite by AI TIME.
2022.01, I start a Research Intern at Tencent AI Lab.
2021.12, Our paper on zero-shot learning is accepted to AAAI'22.
2021.09, Our paper on zero-shot learning is accepted to NeurIPS'21.
2021.07, Our paper on zero-shot learning is accepted to ICCV'21.

Researches

A key challenge of artificial intelligence is to generalize machine learning models from seen data to unseen scenarios. Zero-shot learning (ZSL) is a typical research topic targeting this goal. ZSL aims to classify the images of unseen classes by constructing a mapping relationship between the semantic and visual domains. Although ZSL has achieved significant progress, there have a numbers of essential challenges. Recently, large-scale VLM-based ZSL method is popular, e.g., CLIP, it is an extension of the classical ZSL.

Dr. Shiming Chen has been focusing on tackling bottleneck challenges to promote ZSL (especially for the classical ZSL), covering fundamental questions of How to enhance the visual features by alleviating the cross-dataset bias between ImageNet and ZSL benchmarks? How to discover the intrinsic semantic knowledge by alleviating the visual-semantic domain shift problem? How to align the visual and semantic features in a common space by reducing the discrepancy between the heterogeneous visual-semantic representations? Specifically, his three representatives research projects are:

1. Developing the visual feature enhancement algorithms to tackle the challenge of cross-dataset bias in ZSL. As for the embedding-based ZSL, a graph-guided dual attention network is introduced to fuse the local visual features and explicit global visual features to enhance visual features. As for the generative ZSL, several feature refinement learning methods are proposed to enhance the visual features and encourage the generator to synthesize realistic visual features for unseen classes. The papers of this project have been published in ICCV'21, IJCAI'22, IEEE TNNLS'22, etc.

2. Developing the effective ZSL algorithms to tackle the visual-semantic domain shift problem. As for the embedding-based ZSL, a attribute-guided Transformer network and mutually semantic distillation network are proposed to learn the intrinsic semantic knowledge, enriching the visual features with semantic information to enable desirable semantic knowledge transfer from seen calsses to unseen ones. As for the generative ZSL, dynamic semantic prototype learning is proposed to refine the pre-defined semantic prototypes under the guidance of visual signal, aligning the empirical and actual semantic prototypes for synthesizing accurate visual features. The papers of this project have been published in CVPR'22, AAAI'22, IEEE TPAMI'22, IEEE TEC'23, ICML'23 , etc.

3. Developing the hierarchical semantic-visual adaptation framework for visual-semantic alignment. Different to existing one-step adaptation method that on alignment the feature distributions between visual and semantic domains, this method utilizes a hierarchical adaptation to learn an intrinsic common space for semantic and visual feature representations by adopting sequential structure adaptation and distribution adaptation. The papers of this project have been published in NeurIPS'21.

Selected Publications (Google Scholar)
(*:Co-First Author; #:Corresponding Author)
Survey Papers

Emerging Synergies in Causality and Deep Generative Models: A Survey. [arXiv]
Guanglin Zhou, Shaoan Xie, Guangyuan Hao, Shiming Chen, Biwei Huang, Xiwei Xu, Chen Wang, Liming Zhu, Lina Yao, Kun Zhang.

arXiv preprint arxiv:2301.12351, 2023. (Major Revision on TKDE)

Few-shot object detection: Research advances and challenges. [PDF] [arXiv]
Zhimeng Xin,Shiming Chen, Tianxu Wu, Yuanjie Shao, Weiping Ding, Xinge You.

Information Fusion, 2024. (SCI, IF=18.6)

Conference Papers

Progressive Semantic-Guided Vision Transformer for Zero-Shot Learning. [arXiv]
Shiming Chen, Wenjin Hou, Salman Khan, Fahad Shahbaz Khan.

IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ), 2024. (CCF Rank-A)

Evolving Semantic Prototype Improves Generative Zero-Shot Learning. [PDF] [arXiv]
Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang.

The Fortieth International Conference on Machine Learning ( ICML ), 2023. (CCF Rank-A)

MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning. [PDF] [arXiv] [Code]

Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You.

IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ), 2022: 7612-7621. (CCF Rank-A)

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning. [PDF] [arXiv] [Code]

Shiming Chen, Guo-Sen Xie, Qinmu Peng, Yang Liu, Baigui Sun, Hao Li, Xinge You, Ling Shao.

Annual Conference on Neural Information Processing Systems ( NeurIPS ), 2021: 16622-16634. (CCF Rank-A)

FREE: Feature Refinement for Generalized Zero-shot Learning. [PDF] [arXiv] [Code]

Shiming Chen, Wenjie Wang, Beihao Xia, Qinmu Peng, Xinge You, Feng Zheng, Ling Shao.

IEEE International Conference on Computer Vision ( ICCV ), 2021: 1106-1112. (CCF Rank-A)

TransZero: Attribute-guided Transformer for Zero-Shot Learning. [PDF] [arXiv] [Code]

Shiming Chen^*, Ziming Hong^*, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You.

Thirty-Sixth AAAI Conference on Artificial Intelligence ( AAAI ), 2022: 330-338. (CCF Rank-A)

Semantic Compression Embedding for Generative Zero-Shot Learning.

Ziming Hong*, Shiming Chen^*#, Guo-Sen Xie, Wenhan Yang, Jian Zhao, Yuanjie Shao, Qinmu Peng, Xinge You

The 31th International Joint Conference on Artificial Intelligence ( IJCAI ), 2022: 956-963. (CCF Rank-A)

Journal Papers

TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning. [Project Page] [arXiv] [PDF]

Shiming Chen, Ziming Hong, Wenjin Hou, Guo-Sen Xie, Yibing Song, Jian Zhao, Xinge You, Shuicheng Yan, Ling Shao.

IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI ), 45(11):12844-12861, 2023. (SCI, IF=24.314, CCF Rank-A)

EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning. [PDF] [arXiv]

Shiming Chen, Shuhuang Chen, Wenjin Hou,Weiping Ding, Xinge You.

IEEE Transactions on Evolutionary Computation ( TEC ), in press, 2023. (SCI, IF=14.3, CCF Rank-B)

GNDAN: Graph Navigated Dual Attention Network for Zero-Shot Learning. [Code] [PDF]

Shiming Chen, Ziming Hong, Guo-Sen Xie, Xinge You, Weiping Ding and Ling Shao.

IEEE Transactions on Neural Networks and Learning Systems ( TNNLS), in press, 2022. (SCI, IF=14.255, CCF Rank-B)

CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network. [PDF] [arXiv]

Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Qinmu Peng, Zehong Cao, Weiping Ding.

IEEE Transactions on Evolutionary Computation ( TEC ), 25:986-1000, 2021. (SCI, IF=14.3, CCF Rank-B)

Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis. [Code] [arXiv]

Shiming Chen, Peng Zhang, Guo-sen Xie, Zehong Cao, Qinmu Peng, Wei Yuan, Xinge You.

IEEE Transactions on Systems, Man and Cybernetics: Systems ( TSMCA), 53(2):824-837, 2023. (SCI, IF=11.471)

Awards

2022.08, Huawei Academic Star.

2022.10, China National Scholarship.

Work Experience

Trustworthy Machine Learning Lab (TML Lab), Uinversity of Sydney, Working with Prof. Tongliang Liu

April. 2022 – Dec. 2022

Visiting Student
Topic: Zero-shot Learning, Noisy Label

Tencent, AI Lab.

Jan. 2022 – Dec. 2022

Research Intern
Topic: Zero-shot Learning, Visual-and-Language System

Alibaba DAMO Academy, Machine Intelligence, Vision Lab. Hosted by Rong Jin

May. 2021 – Oct. 2021

Research Intern
Topic: Zero-shot Learning, Domain Adaptation, Transformer

Fortsense, In-Screen Fingerprint Group.

Apr. 2020 – Sep. 2020

Research Intern
Topic: Image Retrieval, Signal Verification

Professional Services

Area Chair: PRCV'23, VALSE.
Journal Reviewers: TPAMI, IJCV, TIP, TNNLS, TEC, TCYB, TSMCA, TITS, TII, TMM, TASE, TIV, etc.
Conference PC/Reviewers: ICLR'23-24, NeurIPS'23, CVPR'22-24, ICCV'21-23, ECCV'22-24, AAAI'22-24, IJCAI'21-23, ACM MM'21.

Invited Talks

School of Information Science and Technology, University of Science and Technology of China

Jun. 2023

Title: Zero-Shot Learning in Vision

Alibaba DAMO Academic

Apr. 2023

Title: Semantic-Guided Zero-Shot Learning

Department of Mathematics and Statistics, Huazhong Agricultural Univeristy

Apr. 2023

Title: Attribute Based Zero-Shot Learning

School of Computer Science and Technology, Guizhou University

Apr. 2023

Title: Semantic-Guided Zero-Shot Learning

National Key Laboratory of Science and Technology on Multispectral Information Processing

Mar. 2023

Title: Deep Feature Representations Based Zero-Shot Learning

IEEE International Conference on Digital Twins and Parallel Intelligence

Nov. 2022

Title: Mutually Semantic Distillation Network for Zero-Shot Learning

Huawei (Shanghai)

Aug. 2022

Title: Deep Feature Representations Based Zero-Shot Image Classification

Zhidongxi (AI New Youth)

Aug. 2022

Title: MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning

VALSE

Jun. 2022

Title: Mutually Semantic Distillation Network for Zero-Shot Learning

AI Drive

Jun. 2022

Title: Mutually Semantic Distillation Network for Zero-Shot Learning

AI TIME

Jun. 2022

Title: Attribute-guided Transformer for Zero-Shot Learning

Extreme Mart

Feb. 2022

Title: Research on Key Technology for Zero-shot Learning

AI TIME

Feb. 2022

Title: 基于层次适应的零样本学习

CVTE

Dec. 2021

Title: Recent Advances in Zero-Shot Learning

Tencent AI Lab

Dec. 2021

Title: The Frontiers in Zero-Shot Learning

Alibaba DAMO Academic

Aug. 2021

Title: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning

© Shiming Chen | Last updated: Sept. 20, 2023

	Progressive Semantic-Guided Vision Transformer for Zero-Shot Learning. [arXiv] Shiming Chen, Wenjin Hou, Salman Khan, Fahad Shahbaz Khan. IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ), 2024. (CCF Rank-A)
	Evolving Semantic Prototype Improves Generative Zero-Shot Learning. [PDF] [arXiv] Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang. The Fortieth International Conference on Machine Learning ( ICML ), 2023. (CCF Rank-A)
	MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning. [PDF] [arXiv] [Code] Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You. IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ), 2022: 7612-7621. (CCF Rank-A)
	HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning. [PDF] [arXiv] [Code] Shiming Chen, Guo-Sen Xie, Qinmu Peng, Yang Liu, Baigui Sun, Hao Li, Xinge You, Ling Shao. Annual Conference on Neural Information Processing Systems ( NeurIPS ), 2021: 16622-16634. (CCF Rank-A)
	FREE: Feature Refinement for Generalized Zero-shot Learning. [PDF] [arXiv] [Code] Shiming Chen, Wenjie Wang, Beihao Xia, Qinmu Peng, Xinge You, Feng Zheng, Ling Shao. IEEE International Conference on Computer Vision ( ICCV ), 2021: 1106-1112. (CCF Rank-A)
	TransZero: Attribute-guided Transformer for Zero-Shot Learning. [PDF] [arXiv] [Code] Shiming Chen^, Ziming Hong^, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You. Thirty-Sixth AAAI Conference on Artificial Intelligence ( AAAI ), 2022: 330-338. (CCF Rank-A)
	Semantic Compression Embedding for Generative Zero-Shot Learning. Ziming Hong, Shiming Chen^#, Guo-Sen Xie, Wenhan Yang, Jian Zhao, Yuanjie Shao, Qinmu Peng, Xinge You The 31th International Joint Conference on Artificial Intelligence ( IJCAI ), 2022: 956-963. (CCF Rank-A)**

	TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning. [Project Page] [arXiv] [PDF] Shiming Chen, Ziming Hong, Wenjin Hou, Guo-Sen Xie, Yibing Song, Jian Zhao, Xinge You, Shuicheng Yan, Ling Shao. IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI ), 45(11):12844-12861, 2023. (SCI, IF=24.314, CCF Rank-A)
	EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning. [PDF] [arXiv] Shiming Chen, Shuhuang Chen, Wenjin Hou,Weiping Ding, Xinge You. IEEE Transactions on Evolutionary Computation ( TEC ), in press, 2023. (SCI, IF=14.3, CCF Rank-B)
	GNDAN: Graph Navigated Dual Attention Network for Zero-Shot Learning. [Code] [PDF] Shiming Chen, Ziming Hong, Guo-Sen Xie, Xinge You, Weiping Ding and Ling Shao. IEEE Transactions on Neural Networks and Learning Systems ( TNNLS), in press, 2022. (SCI, IF=14.255, CCF Rank-B)
	CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network. [PDF] [arXiv] Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Qinmu Peng, Zehong Cao, Weiping Ding. IEEE Transactions on Evolutionary Computation ( TEC ), 25:986-1000, 2021. (SCI, IF=14.3, CCF Rank-B)
	Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis. [Code] [arXiv] Shiming Chen, Peng Zhang, Guo-sen Xie, Zehong Cao, Qinmu Peng, Wei Yuan, Xinge You. IEEE Transactions on Systems, Man and Cybernetics: Systems ( TSMCA), 53(2):824-837, 2023. (SCI, IF=11.471)