Neehar Peri

Neehar Peri

Computer Vision & Machine Learning Researcher

Towards 3D Perception In-The-Wild

I am a fourth year PhD candidate working on Computer Vision at Carnegie Mellon University. My current work with the Center for Autonomous Vehicle Research focuses on building robust 3D perception algorithms for detection, tracking, forecasting, planning, and simulation. I am supported in part by a NSF Graduate Research Fellowship.

I am advised by Deva Ramanan at the Robotics Institute and frequently collaborate with Shu Kong, James Hays, and Laura Leal-Taixe. As an undergraduate at the University of Maryland, I was involved in research under the guidance of Rama Chellappa and John Dickerson.

Formal Biography Neehar Peri is a fourth year Robotics Ph.D. candidate at Carnegie Mellon University. He is broadly interested in computer vision and machine learning, with applications to robot perception and action. His work has been published at conferences including CVPR, ICCV, ECCV, NeurIPS, ICLR, and CoRL. He graduated from the University of Maryland in 2021 with a Bachelor’s degree in Computer Engineering. He was awarded the Sujan Guha Memorial best senior thesis, and was recognized as a Maryland Undergraduate Researcher of the Year. His work is supported in part by a NSF Graduate Research Fellowship.

Recent News

  • [September 2024] Our paper Revisiting Few-Shot Object Detection with Vision-Language Models has been accepted to NeurIPS D&B 2024
  • [September 2024] Our paper Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection has been accepted to CoRL 2024
  • [July 2024] Our paper Better Call SAL: Towards Segmenting Anything in LiDAR has been accepted to ECCV 2024
  • [July 2024] Our paper I Can’t Believe It’s Not Scene Flow has been accepted to ECCV 2024
  • [May 2024] Our paper Semi-Supervised Federated Multi-Organ Segmentation with Partial Labels has been accepted to AAPM 2024
  • [January 2024] Our paper ZeroFlow: Scalable Scene Flow via Distillation has been accepted to ICLR 2024
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  • [August 2023] Our paper An Empirical Analysis of Range for 3D Object Detection has been accepted to BRAVO @ ICCV 2023
  • [March 2023] I was awarded the NSF Graduate Research Fellowship
  • [March 2023] Our paper ReBound: An Open-Source 3D Bounding Box Annotation Tool for Active Learning has been accepted to AutomationXP @ CHI 2023
  • [January 2023] Our paper Data and Algorithms for End-to-End Thermal Spectrum Face Verification has been accepted to TBIOM 2022
  • [September 2022] Our paper Towards Long Tailed 3D Detection has been accepted to CoRL 2022
  • [August 2022] Our paper A Brief Survey of Person Recognition at a Distance has been accepted to ACSSC 2022
  • [March 2022] Our paper Forecasting from LiDAR via Future Object Detection has been accepted to CVPR 2022
  • [February 2022] Our paper Assessment of a Novel Virtual Environment for Examining Human Cognitive-Motor Performance during Execution of Action Sequences has been accepted to HCII 2022
  • [October 2021] Our paper A Synthesis-Based Approach for Thermal-to-Visible Face Verification has been accepted to FG 2021
  • [September 2021] Our paper PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning has been accepted to NeurIPS 2021
  • [May 2021] I was selected as one of Maryland's Undergraduate Researchers of the Year
  • [May 2021] I was awarded the Sujan Guhan Memorial Best Senior Thesis by UMD's ECE Department
  • [December 2020] I was awarded an honorable mention for the Computing Research Association's Outstanding Undergraduate Researcher Award