Chenxun Deng
Chenxun Deng profile photo from Google Scholar

Ph.D. Student

Chenxun Deng

Institute of Automation, Chinese Academy of Sciences

I work on computer vision and machine learning, with a focus on long-tailed recognition, diffusion models, wildlife visual understanding, and vision-language systems for scientific image analysis.

Synced from Scholar 6 publications
Primary directions Vision and learning
Profile status ia.ac.cn verified

Research Interests

Computer Vision Long-Tailed Learning Diffusion Models Wildlife Recognition Vision-Language Modeling Scientific Image Analysis

Publications

Representative graphic for ChatDiff
Neural Networks, 2025

ChatDiff: A ChatGPT-based diffusion model for long-tailed classification

C. Deng, D. Li, L. Ji, C. Zhang, B. Li, H. Yan, J. Zheng, L. Wang, J. Zhang

Combines language-guided prompting and diffusion-based generation to improve recognition under long-tailed class distributions.

Representative graphic for DeLoCo
Ecological Informatics, 2025

DeLoCo: Decoupled location context-guided framework for wildlife species classification using camera trap images

L. Wang, S. Wang, C. Deng, H. Zhu, Y. Tian, J. Zhang

Uses location context to support camera-trap wildlife recognition in complex ecological scenes.

Representative graphic for hypergraph-driven spatial multimodal fusion
Communications Biology, 2025

Hypergraph-driven spatial multimodal fusion for precise domain delineation and tumor microenvironment decoding

C. Zhang, X. Li, B. Li, C. Deng, M. Li, S. Zhang, W. Yu, H. Zhang, Z. Wang, et al.

Models spatial multimodal biological data with hypergraph fusion for domain delineation and microenvironment analysis.

Representative graphic for PGMM
Pattern Recognition, 2026

PGMM: Prior Guided Multi-expert Model for Long-tailed Classification

C. Deng, L. Ji, C. Zhang, H. Yan, Z. Zhang, L. Wang, J. Zhang

Introduces prior-guided expert specialization for more robust long-tailed visual classification.

Representative graphic for SDNet
Avian Research, 2026

SDNet: A self-supervised bird recognition method based on large language models and diffusion models for improving long-term bird monitoring

Z. Zhang, N. Su, C. Deng, Y. Zhao, W. Liu, Q. Han

Connects self-supervised visual learning with language and diffusion priors for long-term bird monitoring.

Representative graphic for SAVIOR
Neurocomputing, 2026

SAVIOR: Assessing volume alignment quality for serial section electron microscopy images using large vision-language model

H. Chen, C. Deng, B. Chen, Y. Lv, X. Chen, H. Han

Applies large vision-language modeling to assess alignment quality in serial-section electron microscopy volumes.