Improving Process Efficiency at Cherehani Africa
Published:
Posts by Collection
portfolio
Analyzing Reddit Feeds with Data Science
Published:
Scene Recognition with Limited Data
Published:
CVPR 2023 End-to-End Forecasting Challenge
Published:
CVPR 2024 End-to-End Forecasting Challenge
Published:
publications
Attention Driven Vehicle Re-ID and Unsupervised Anomaly Detection for Traffic Understanding
Published in CVPRW - NVIDIA AI City Challenge, 2019
Recommended Citation: Khorramshahi P, Peri N, Kumar A, Shah A, Chellappa R. Attention Driven Vehicle Re-ID and Unsupervised Anomaly Detection for Traffic Understanding. In: Computer Vision and Pattern Recognition Workshops, CVPRW 2019
A Dual-Path Model with Adaptive Attention for Vehicle Re-ID
Published in ICCV, 2019
Recommended Citation: Khorramshahi P, Kumar A, Peri N, Rambhatla SS, Chen JC, Chellappa R. A Dual-Path Model with Adaptive Attention for Vehicle Re-ID. In: International Conference on Computer Vision, ICCV 2019
Towards Real-Time Systems for Vehicle Re-ID, Multi-Camera Tracking, and Anomaly Detection
Published in CVPRW - NVIDIA AI City Challenge, 2020
Recommended Citation: Peri N, Khorramshahi P, Rambhatla SS, Shenoy V, Rawat S, Chen JC, Chellappa R. Towards Real-Time Systems for Vehicle Re-ID, Multi-Camera Tracking, and Anomaly Detection. In: Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Deep K-NN Defense against Clean-Label Data Poisoning Attacks
Published in ECCVW - Adversarial Robustness in the Real World, 2020
Recommended Citation: Peri N, Gupta N, Huang WR, Fowl L, Zhu C, Feizi S, Goldstein T, Dickerson JP. Deep k-NN Defense against Clean-Label Data Poisoning Attacks. In: European Conference on Computer Vision Workshops, ECCVW 2020
The Devil is in the Details: Self-Supervised Attention for Vehicle Re-ID
Published in ECCV, 2020
Recommended Citation: Khorramshahi P, Peri N, Chen JC, Chellappa R. The Devil is in the Details: Self-Sueprvised Attention for Vehicle Re-ID. In: European Conference on Computer Vision, ECCV 2020
A Synthesis Based Approach for Thermal-to-Visible Face Verification
Published in FG, 2021
Recommended Citation: Peri N, Gleason J, Castillo CD, Bourlai T. Patel VM, Chellappa R. A Synthesis Based Approach for Thermal-to-Visible Face Verification. In: IEEE International Conference on Automatic Face and Gesture Recognition, FG 2021
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning
Published in NeurIPS, 2021
Recommended Citation: Peri N, Curry MJ, Dooley S, Dickerson JP. PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. In: Neural Information Processing Systems, NeurIPS 2021
Assessment of a Novel Virtual Environment for Examining Human Cognitive-Motor Performance during Execution of Action Sequences
Published in HCII, 2022
Recommended Citation: Shaver A, Peri N, Mezebish R, Matthew G, Berson A, Gaskins C, Davis GP, Katz GE, Samuel I, Reinhard MJ, Costanzo ME, Reggia JA, Purtilo J, Gentili RJ. Assessment of a Novel Virtual Environment for Examining Human Cognitive-Motor Performance during Execution of Action Sequences. In: International Conference on Human Computer Interaction, HCII 2022
Forecasting from LiDAR via Future Object Detection
Published in CVPR, 2022
Recommended Citation: Peri N, Jonathon Luiten, Mentian Li, Aljosa Osep, Laura Leal-Taixe, Deva Ramanan. Forecasting from LiDAR via Future Object Detection. In: International Conference on Computer Vision and Pattern Recognition, CVPR 2022
Towards Long-Tailed 3D Detection
Published in CoRL, 2022
Recommended Citation: Peri N, Dave A, Ramanan D, Kong S. Towards Long Tailed 3D Detection. In: Conference on Robot Learning, CoRL 2022
MSR Thesis: Long-Tailed 3D Detection via Multi-Modal Fusion
Published in CMU, 2023
Recommended Citation: Peri N. Long-Tailed 3D Detection via Multi-Modal Fusion. Carnegie Mellon University. 2023
An Empirical Analysis of Range for 3D Object Detection
Published in ICCVW, 2023
Recommended Citation: Peri N, Li M, Wilson B, Wang YX, Hays J, Ramanan D. An Empirical Analysis of Range for 3D Object Detection. In: International Conference on Computer Vision Workshops, ICCVW 2023
ZeroFlow: Scalable Scene Flow via Distillation
Published in ICLR, 2024
Recommended Citation: Vedder K, Peri N, Chodosh N, Khatri I, Eaton E, Jayaraman D, Liu Y, Ramanan D, Hays J. ZeroFlow: Scalable Scene Flow via Distillation. In: International Conference on Representation Learning, ICLR 2024
Semi-Supervised Federated Multi-Organ Segmentation with Partial Labels
Published in AAPM, 2024
Recommended Citation: Pemmaraju R, Peri N. Semi-Supervised Federated Multi-Organ Segmentation with Partial Labels. In: American Association of Physicists in Medicine, AAPM 2024
Better Call SAL: Towards Learning to Segment Anything in LiDAR
Published in ECCV, 2024
Recommended Citation: Osep A, Meinhardt T, Ferroni F, Peri N, Ramanan D, Leal-Taixe L. Better Call SAL: Towards Learning to Segment Anything in LiDAR. In: European Conference on Computer Vision, ECCV 2024
I Cant Beleive Its Not Scene Flow!
Published in ECCV, 2024
Recommended Citation: Vedder K, Khatri I, Peri N, Ramanan D, Hays J. I Cant Beleive Its Not Scene Flow! In: European Conference on Computer Vision, ECCV 2024
Long-Tailed 3D Detection via Multi-Modal Fusion
Published in , 2024
Recommended Citation: Ma Y, Peri N, Wei S, Dave A, Hua W, Li Y, Ramanan D, Kong S. Long-Tailed 3D Detection via Multi-Modal Fusion. Under Review at TPAMI
Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection
Published in CoRL, 2024
Recommended Citation: Khurana M, Peri N, Hays J, Ramanan D. Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection. In: Conference on Robot Learning, CoRL 2024
talks
teaching
Undergraduate Teaching Fellow (Spring 2019)
ENEE 244: Introduction to Digital Logic, ECE Department, 2019
- Led recitation for a discussion section of 15 students
- Received highest marks on metrics of preparedness, respect for students, and overall teaching effectiveness from all students
Head Graduate Teaching Assistant (Spring 2022)
16-720B: Computer Vision, Robotics Institute, 2022
- Managed team of teaching assistants to effectively coordinate course responsibilities
- Updated course projects, held office hours, answered student questions and graded course projects
- Presented guest lectures on Training Convolutional Neural Networks and Transformers for Vision
Head Graduate Teaching Assistant (Fall 2022)
16-720A: Computer Vision, Robotics Institute, 2022
- Managed team of teaching assistants to effectively coordinate course responsibilities
- Updated course projects, held office hours, answered student questions and graded course projects
- Presented guest lectures on Image Processing and Convolutions