About me

Hi there! I am a Ph.D. at the Vision and Fusion Laboratory (IES) at Karlsruher Institut of Technologie (KIT), under the supervision of Prof. Jürgen Beyerer. Before that, I was a research scientist at the Institute for Visualization and Data Analysis (IVD) at KIT. I received my master’s degree in Control Science and Engineering and my bachelor’s degree in Automation from Nanjing University (NJU).

My primary research focus is 3D computer vision, spanning both applied and theoretical domains. On the applied side, I am actively involved in the AgiProbot project (feel free to take the virtual tour !), where I handle tasks like point cloud segmentation, synthetic data generation, and sim2real transfer learning. On the theoretical side, my research centers on developing novel algorithms for self-supervised learning, 3D shape generation, and point cloud sampling (feel free to check my CVPR 2023 highlight paper and the recently accepted CVPR 2025 paper ). Beyond 3D vision, I have strong interests in multi-modal learning, scene-level 2D image analysis (e.g. panoramic images), and vision-language models (e.g. open-vocabulary segmentation and video narration). Earlier in my research journey, I also worked on 3D volumetric data synthesis and image style transfer. My master’s thesis was about quantum control.

📖 Selected Publications

• SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformity
• C. Wu, Y. Wan, H. Fu, J. Pfrommer, Z. Zhong, J. Zheng, J. Zhang, and J. Beyerer
• CVPR 2025
• 📄 Paper | 💻 Code | 🏡 Homepage | 🎥 Video

• Open Panoramic Segmentation
• J. Zheng, R. Liu, Y. Chen, K. Peng, C. Wu, K. Yang, J. Zhang, R. Stiefelhagen
• ECCV 2024
• 📄 Paper | 💻 Code | 🏡 Homepage | 🎥 Video

• Attention-based Point Cloud Edge Sampling
• C. Wu, J. Zheng, J. Pfrommer, and J. Beyerer
• CVPR 2023 (Highlight Paper)
• 📄 Paper | 💻 Code | 🏡 Homepage | 🎥 Video

• Sim2real Transfer Learning for Point Cloud Segmentation: An Industrial Application Case on Autonomous Disassembly
• C. Wu, X. Bi, J. Pfrommer, A. Cebulla, S. Mangold, J. Beyerer
• WACV 2023
• 📄 Paper | 💻 Code | 🏡 Homepage | 🎥 Video

• SynMotor: A Benchmark Suite for Object Attribute Regression and Multi-task Learning
• C. Wu, L. Qiu, K. Zhou, J. Pfrommer, J. Beyerer
• VISAPP 2023 (Best Paper Finalist)
• 📄 Paper | 💻 Code | 🏡 Homepage | 🎥 Video

• Self-Supervised Generative-Contrastive Learning of Multi-Modal Euclidean Input for 3D Shape Latent Representations: A Dynamic Switching Approach
• C. Wu, J. Pfrommer, M. Zhou, J. Beyerer
• IEEE TMM
• 📄 Paper | 💻 Code