Peiyun Hu

I am a Software Engineer at Argo AI. I recently completed my Ph.D. in Robotics at Carnegie Mellon University. My thesis can be found here.

Research

My work focuses on improving the robustness and scalability of learning-based perception systems.

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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

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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

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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

We exploit often overlooked freespace in LiDAR-based 3D object detection.

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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

We marry graph search with learning for point cloud optimal segmentation.

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Recognizing Tiny Faces
Siva Chaitanya Mynepalli, Peiyun Hu, Deva Ramanan
Computer Vision and Pattern Recognition Workshops (CVPR-W), 2019
paper

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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

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Active Learning with Partial Feedback
Peiyun Hu, Zack C. Lipton, Anima Anandkumar, Deva Ramanan
International Conference on Learning Representations (ICLR), 2019
paper / poster / code

We formulate AL as a 20Q game between evolving models and human.

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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

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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

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Finding Tiny Faces
Peiyun Hu, Deva Ramanan
Computer Vision and Pattern Recognition (CVPR), 2017
paper / project / video / poster / press / code

We address key challenges in detecting tiny objects with neural nets.

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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

We derive architectures to endow neural nets with top-down reasoning.


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