Peiyun Hu

I am a research scientist at Apple with Vladlen Koltun. I received my PhD in Robotics from the Carnegie Mellon University Robotics Institute, where I was advised by Deva Ramanan. My research lies at the intersection of computer vision and robotics, exploring how machines can perceive and anticipate the world around them, from recognizing subtle visual details to reasoning about 3D structure and anticipating how the world unfolds over time. Prior to my current role, I worked at Argo AI and later at Apple SPG.

	CoMotion: Concurrent Multi-person 3D Motion Alejandro Newell, Peiyun Hu, Lahav Lipson, Stephan Richter, Vladlen Koltun International Conference on Learning Representations (ICLR), 2025 paper / code
	Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting Tarasha Khurana, Peiyun Hu**, David Held, Deva Ramanan Computer Vision and Pattern Recognition (CVPR), 2023 paper / project / talk / code
	Differentiable Raycasting for Self-Supervised Planning Tarasha Khurana, Peiyun Hu**, Achal Dave, Jason Ziglar, David Held, Deva Ramanan European Conference on Computer Vision (ECCV), 2022 paper / project / code
	Safe Local Motion Planning with Self-Supervised Freespace Forecasting Peiyun Hu, Aaron Huang, John Dolan, David Held, Deva Ramanan Computer Vision and Pattern Recognition (CVPR), 2021 paper / project / poster / talk / code
	Active Perception using Light Curtains for Autonomous Driving Siddharth Ancha, Yaadhav Raaj, Peiyun Hu, Srinivasa Narasimhan, David Held European Conference on Computer Vision (ECCV), 2020 (Spotlight Presentation) paper / project / slides / talk / code
	What You See is What You Get: Exploiting Visibility for 3D Object Detection Peiyun Hu, Jason Ziglar, David Held, Deva Ramanan Computer Vision and Pattern Recognition (CVPR), 2020 (Oral Presentation) paper / project / slides / talk / demo / code
	Learning to Optimally Segment Point Clouds Peiyun Hu, David Held, Deva Ramanan IEEE Robotics and Automation Letters (RA-L) and ICRA, 2020 paper / project / slides / talk / demo / code
	Recognizing Tiny Faces Siva Chaitanya Mynepalli, Peiyun Hu, Deva Ramanan Computer Vision and Pattern Recognition Workshops (CVPR-W), 2019 paper
	Inferring Distributions Over Depth from a Single Image Gengshan Yang, Peiyun Hu, Deva Ramanan IEEE International Conference on Intelligent Robots and Systems (IROS), 2019 paper / project / slides / code
	Active Learning with Partial Feedback Peiyun Hu, Zack C. Lipton, Anima Anandkumar, Deva Ramanan International International Conference on Learning Representations (ICLR), 2019 paper / poster / code
	Camera-based Semantic Enhanced Vehicle Segmentation for Planar LIDAR Chen Fu, Peiyun Hu, Chiyu Dong, Christoph Mertz, John Dolan International Conference on Intelligent Transportation Systems (ISTC), 2018 paper
	Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset Zachary Pezzementi, Trenton Tabor, Peiyun Hu, Jonathan K. Chang, Deva Ramanan, Carl Wellington, Benzun P. Wisely Babu, Herman Herman Journal of Field Robotics (JFR), 2018 paper / project / video
	Unconstrained Face Detection and Open-Set Face Recognition Challenge Manuel Gunther, Peiyun Hu, Christian Herrmann, Chi-Ho Chan, Min Jiang, Shufan Yang, Akshay Raj Dhamija, Deva Ramanan, Jurgen Beyerer, Josef Kittler, Mohamad Al Jazaery, Mohammad Iqbal Nouyed, Guodong Guo, Cezary Stankiewicz, Terrance E Boult IEEE International Joint Conference on Biometrics (IJCB), 2017 paper
	Finding Tiny Faces Peiyun Hu, Deva Ramanan Computer Vision and Pattern Recognition (CVPR), 2017 paper / project / video / poster / press / code
	Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians Peiyun Hu, Deva Ramanan Computer Vision and Pattern Recognition (CVPR), 2016 (Spotlight Presentation) paper / project / ext. abstract / slides / talk / poster / code

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