I am Anpeng Wang (王安鹏), currently an undergraduate student majoring in Robotics Engineering at the School of Control Science and Engineering, Shandong University. Academically, I am fortunate to study under the supervision of Professor Runmin Cong and am now affiliated with Multimedia and Vision Processing Group (MVP Group), which is attached to the Key Laboratory of Machine Intelligence and System Control, Ministry of Education.
My core research interests focus on Few-shot Learning. Currently, I am conducting relevant exploratory work around these research directions.
Regarding my future academic plan, I have decided to continue pursuing a Master’s degree at the School of Control Science and Engineering, Shandong University starting from 2026, where I will continue to delve deeply into the aforementioned research fields.
If you are interested in any form of academic cooperation, please feel free to contact me via email: [email protected].
🔥 News
- 2026.03: 🎉🎉🎉 A paper has been accepted by IEEE ICME 2026!
- 2026.02: 🎉🎉🎉 A cooperative paper has been accepted by CVPR 2026!
- 2026.01: Attend AAAI 2026 in Singapore and give an oral presentation.
- 2025.11: 🎉🎉🎉 My first paper has been accepted by AAAI 2026 (Oral)!
📝 Publications
Divide-and-Conquer Decoupled Network for Cross-Domain Few-Shot Segmentation
Runmin Cong, Anpeng Wang, Bin Wan, Cong Zhang, Xiaofei Zhou, Wei Zhang
- This paper focuses on Cross-Domain Few-Shot Segmentation, leveraging feature disentanglement enabled by contrastive-adversarial learning.
ADSeeker: A Knowledge-Grounded Reasoning Framework for Industry Anomaly Detection and Reasoning
Kai Zhang, Zekai Zhang, Xihe Sun, Anpeng Wang, et al.
- This paper proposes the ADSeeker framework to improve fine-grained reasoning and zero-shot performance for industrial anomaly detection.
- We construct the first visual document knowledge base SEEK-M&V and the largest anomaly detection dataset MulA to address data scarcity and insufficient type-level annotations.
P³-SAM: SAM with Perceptual Parallel Prompt for Few-Shot Strip Steel Surface Defect Segmentation
Qian Xu, Hang Xiong, Anpeng Wang*, et al. ( * corresponding author )
- This paper proposes the P³-SAM model, which optimizes SAM via two core strategies of POE and PPG to address the challenges of few-shot strip steel surface defect segmentation.
🎖 Honors and Awards
- 2024.09 Shandong University Outstanding Student Scholarship
- 2024.07 Shandong University Innovation and Entrepreneurship Scholarship
- 2023.12 APMCM Asia-Pacific Mathematical Contest in Modeling First Prize
- 2023.09 Shandong University Outstanding Student Scholarship
- 2023.08 National University Students Intellingent Car Race National Second Prize
📖 Educations
- 2026.09 (future), Master, School of Control Science and Engineering, Shandong University, Jinan, China. Advisor: Prof. Runmin Cong
- 2022.09 - 2026.07 (now), Undergraduate, School of Control Science and Engineering, Shandong University, Jinan, China. Advisor: Prof. Runmin Cong
💻 Professional Services
- 2026, Reviewer for IEEE International Conference on Multimedia and Expo (ICME’26)
- 2025, Reviewer for Association for the Advancement of Artificial Intelligence (AAAI’26)