Haoxing Chen

DeepLearning Lab,
Ant Research Institute,
Hangzhou, CHINA

"Everything should be made as simple as possible, but no simpler." — Albert Einstein

About Me

I am an Artificial Intelligence Research Fellow with DeepLearning Lab at Ant Research Institute, which is under the leadership of CTO Zhengyu He. My research benefits from collaboration with esteemed colleagues including Dr. Jianguo Li, Dr. Yaohui Li, Dr. Zhangxuan Gu, Dr. Yan Hong, and Scientist Zhuoer Xu.

I pursued my M.E. in Automation and Artificial Intelligence Group at Nanjing University (NJU), where I was mentored by Prof. Chunlin Chen and Prof. Huaxiong Li. My B.E. was obtained at Southeast University (SEU). My research interests include few-shot learning, image generation, self-supervised learning, computer vision, and machine learning. Currently, I focus on Representation Learning, AIGC, and Learning with Limited Data.

News

  • [Mar./2025]: I have joined the DeepLearning Lab at Ant Research Institute to pursue cutting-edge research in Artificial General Intelligence (AGI).
  • [Feb/2025]: One paper on “Multi-modal foundation models” is accepted to CVPR 2025.
  • [Dec/2024]: One paper on “AIGC detection” is accepted to AAAI 2025 as Oral representation.
  • [July/2024]: One paper on “Multi-view clustering” is accepted to Pattern Recognition.
  • [July/2024]: We showcased our achievements (HDNet/DiffUTE/DeMamba/etc.) in generation and detection at the World Artificial Intelligence Conference.
  • [July/2024]: One paper on “AIGC” is accepted to ECCV 2024.
  • [Dec./2023]: Two paper on “Diffusion model” and “Image composition” is accepted to ICASSP 2024.
  • [Sep./2023]: One paper on “AIGC” is accepted to NeurIPS 2023.
  • [Aug/2023]: We won 2nd place (2/717) in the tamper-proof financial documents track in the AFAC Financial Data Verification Competition
  • [July/2023]: One paper on “Image composition” is accepted to ACM Multimedia 2023 as Oral representation.
  • [April/2023]: One paper on “Contrastive learning” is accepted to ICML 2023.
  • [Mar./2023]: We won 3rd place (3/1267) in the classification track and 6th place (6/1156) in the detection track in the ICDAR Detecting Tampered Text in Images Competition.
  • [Feb./2023]: One paper on “Vision-language learning” is accepted to CVPR 2023.
  • [Jan./2023]: One paper on “Few-shot learning” is accepted to SCIS 2023.
  • [July/2022]: One paper on “Affective computing” is accepted to ACM Multimedia 2022.

Research Interest

I work in the field of few-shot learning, image generation, self-supervised learning, computer vision and machine learning. Currently, I focus on the following research topics:
  • Representation Learning: Representation learning aims to discover abstract descriptions of concepts. Specifically, Haoxing focuses on enhancing the universality of the model through self-supervised learning and multimodal learning.
  • AIGC: How to design better defense systems to deal with generated attacks has gained extensive attention in recent years. Specifically, Haoxing trys to generate more realistic images and design better detection methods with multi-modal learning.
  • Learning with Limited Data: The ability of a model to fit with limited data is essential and necessary due to the instance/label collection cost. How to extract and utilize knowledge from related tasks and domains is the key. Specifically, Haoxing mainly works on how to learn meta-knowledge for zero-/few-shot learning.

Experiences

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AI Researcher | DeepLearning Lab, Ant Research Institute
Mar 2025 - Present.

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AI Researcher | Tiansuan Lab, Ant Group
May 2022 - Mar 2025

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Undergraduate Student | South East University
Sep 2016 - June 2020.

Selected Publications [Full List] [Google Scholar] [DBLP]

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Efficient Transfer Learning for Video-language Foundation Models
Haoxing Chen, Zizheng Huang, Yan Hong, Yanshuo Wang, Zhongcai Lyu, Zhuoer Xu, Jun Lan, Zhangxuan Gu. In: IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2025. (CCF-A)
[Paper]

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WildFake: A Large-scale Challenging Dataset for AI-Generated Images Detection
Yan Hong, Jianming Feng, Haoxing Chen, Jun Lan, Huijia Zhu, Weiqiang Wang, Jianfu Zhang.
In: AAAI Conference on Artificial Intelligence (AAAI), 2025.(CCF-A) Oral
[Data]

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Learning Latent Distangled Embeddings and Graphs for Multi-view Clustering
Chao Zhang, Haoxing Chen, Huaxiong Li, Chunlin Chen.
Pattern Recognit., 2024. (CCF-B, SCI/SCIE, Impact Factor: 7.5)
[Paper]

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ComFusion: Personalized Subject Generation in Multiple Specific Scenes From Single Image
Yan Hong, Yuxuan Duan, Bo Zhang, Haoxing Chen, Jun Lan, Huijia Zhu, Weiqiang Wang, Jianfu Zhang.
In: European Conference on Computer Vision (ECCV), 2024.(CCF-B)

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Segment Anything Model Meets Image Harmonization
Haoxing Chen, Yaohui Li,, Zhangxuan Gu, Zhuoer Xu, Jun Lan, Huaxiong Li.
In: IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP), 2024. (CCF-B)
[Paper] [arXiv] [BibTex]

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DiffusionInst: Diffusion Model for Instance Segmentation
Zhangxuan Gu, Haoxing Chen, Zhuoer Xu, Jun Lan, Changhua Meng, Weiqiang Wang.
In: IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP), 2024. (CCF-B) Oral
[Paper] [arXiv] [Code] [Code(Ant-Research)] [BibTex] 200+ GitHub Stars

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DiffUTE: Universal Text Editing Diffusion Model
Haoxing Chen, Zhuoer Xu, Zhangxuan Gu, Jun Lan, Xing Zheng, Yaohui Li, Changhua Meng, Huijia Zhu, Weiqiang Wang.
In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. (CCF-A)
[Paper] [arXiv] [Code] [Video] 100+ GitHub Stars

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Hierarchical Dynamic Image Harmonization
Haoxing Chen, Zhangxuan Gu, Yaohui Li, Jun Lan, Changhua Meng, Weiqiang Wang, Huaxiong Li.
In: ACM Multimedia (ACM MM), 2023. (CCF-A) Oral
[Paper] [arXiv] [Code] [BibTex]

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Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
Zizheng Huang#, Haoxing Chen #* , Ziqi Wen, Chao Zhang, Huaxiong Li, Bo Wang, Chunlin Chen. In: International Conference on Machine Learning(ICML), 2023. (CCF-A) [# Equal contribution, * Corresponding author]
[Paper] [arXiv] [Code]

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Sparse Spatial Transformers for Few-Shot Learning
Haoxing Chen, Huaxiong Li, Yaohui Li, Chunlin Chen. Sci. China Inf. Sci., 2023, 66(11): 210102. (CCF-A, SCI/SCIE, Impact Factor: 8.8)
[Paper] [SCIS Link] [Code]

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Mobile User Interface Element Detection Via Adaptively Prompt Tuning
Zhangxuan Gu, Zhuoer Xu, Haoxing Chen, Jun Lan, Changhua Meng, Weiqiang Wang. In: IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2023. (CCF-A)
[Paper] [CVPR Link] [Code] [BibTex]

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Transductive Aesthetic Preference Propagation for Personalized Image Aesthetics Assessment
Yaohui Li, Yuzhe Yang, Huaxiong Li, Haoxing Chen, Liwu Xu, Leida Li, Yaqian Li, Yandong Guo. In: ACM Multimedia (ACM MM), 2022. (CCF-A)
[Paper] [BibTex]

Awards

  • 2023, 2nd place (2/717) in the tamper-proof financial documents track in the AFAC Financial Data Verification Competition.
  • 2023, Nanjing University (NJU) Outstanding Graduates.
  • 2023, 3rd place (3/1267) in the classification track and 6th place (6/1156) in the detection track in the ICDAR Detecting Tampered Text in Images Competition.
  • 2022, Chinese National Scholarship.
  • 2019, Meritorious Prize in the Mathematical Contest In Modeling (MCM).
  • 2018, First Prize of Jiangsu Province in the National Mathematical Modelling Competition.
  • 2018, National Special Award of the 8th Education Robot Competition Of China (ERCC).

Services

  • ICLR'25, ICCV'25, CVPR'25, ICME'25, ICML'24/25, NeurIPS'24, WACV'24, ACM MM'23/24, AAAI'23/25, PAKDD'22, ICPR'22, Reviewer
  • IEEE Trans on TIP/TCYB/TMM/TNNLS/TCSVT, Reviewer