Dr. Tao Chen | Object Detection and Recognition | Research Excellence Award
Professor | Fudan University | China
Dr. Tao Chen is a leading researcher at Fudan University, specializing in deep learning and computer vision, with a focus on human motion understanding, 3D shape generation, and semantic segmentation. He has contributed to over 249 high-impact publications in top-tier venues including CVPR, NeurIPS, and IEEE Transactions, accumulating more than 6294 citations. His work integrates advanced neural architectures, motion diffusion, and cross-domain adaptation techniques, often in collaboration with international researchers such as G. Yu and W. Liu. Dr. Chen’s research has significant societal impact, advancing intelligent systems for medical imaging, autonomous perception, and interactive 3D applications, bridging fundamental AI research with practical real-world solutions.
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Featured Publications
Executing your commands via motion diffusion in latent space.
– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . (2023). Cited By : 580
MotionGPT: Human motion as a foreign language. In Advances in Neural Information Processing Systems.
-Curran Associates, Inc. (2023). Cited By: 548
TopFormer: Token pyramid transformer for mobile semantic segmentation.
-In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2022). Cited By: 388
b‑DARTS: Beta‑decay regularization for differentiable architecture search.
– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2022). Cited By: 194
LL3DA: Visual interactive instruction tuning for omni‑3D understanding, reasoning, and planning.
– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2024). Cited By: 178
