Nakul Agarwal

I am a Machine Learning Research Engineer at Honda Research Institute, USA working on challening problems related to computer vision and machine learning with application to Advanced Driver Assistance Systems (ADAS), autonomous navigation and robotics.

I graduated with a M.S. degree in EECS from UC Merced where I was working in the Vision and Learning Lab under the supervision of Prof. Ming-Hsuan Yang. Prior to joining UC Merced as a graduate student, I worked with Prof. C. V. Jawahar and Prof. Vineeth N. Balasubramaniam at Centre for Visual Information Technology in IIIT Hyderabad, India. I received my B.E. (Bachelor of Engineering) degree from Netaji Subhas Institute of Technology, University of Delhi in 2016.

Email  /  CV  /  Google Scholar

News

  • 10 / 2022:   Our paper on "Risk Perception in Driving Scenes" has been accepted at NeurIPS 2022 Workshop on Machine Learning for Autonomous Driving!.
  • 03 / 2022:   Our paper on "Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos" has been accepted at CVPR 2022!.
  • 12 / 2021:   I will be serving as a reviewer for CVPR 2022.
  • 07 / 2020:   One paper on Unsupervised Domain Adaptation accepted in BMVC'20!
  • 03 / 2020:   One paper accepted in CVPR'20 workshop!
  • 08 / 2018:   Our paper on "Connecting Visual Experiences using Max-flow Network with Application to Visual Localization" is out on arXiv!
  • 06 / 2018:   Our paper on "Improving Multiclass Classification by Deep Networks using DAGSVM and Triplet Loss" has been accepted at Pattern Recognition Letters 2018!
  • 05 / 2018:   Started my internship at Honda Research Institute, Mountain View
  • 08 / 2017:   Started my M.S. at UC Merced

Research

Can’t make an Omelette without Breaking some Eggs: Plausible Action Anticipation using Large Video-Language Models
Himangi Mittal, Nakul Agarwal, Shao-Yuan Lo, Kwonjoon Lee
CVPR, 2024
project   paper

Uncertainty-aware Action Decoupling Transformer for Action Anticipation
Hongji Guo, Nakul Agarwal, Shao-Yuan Lo, Kwonjoon Lee, Qiang Ji
CVPR, 2024
project   paper

Vamos: Versatile Action Models for Video Understanding
Shijie Wang, Qi Zhao, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun
Preprint
project   paper

AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao*, Ce Zhang*, Shijie Wang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun
(* equal contribution)
ICLR, 2024
project   paper

Disentangled Neural Relational Inference for Interpretable Motion Prediction
Victoria Magdalena Dax, Jiachen Li, Enna Sachdeva, Nakul Agarwal, Mykel Kochenderfer
RA-L and ICRA, 2024
project   paper

Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning
Enna Sachdeva*, Nakul Agarwal*, Suhas Chundi, Jiachen Li, Mykel Kochenderfer, Chiho Choi, Behzad Dariush,
(* equal contribution)
WACV, 2024
project   paper

Object-centric Video Representation for Long-term Action Anticipation
Ce Zhang*, Changcheng Fu*, Shijie Wang, Nakul Agarwal, Kwonjoon Lee, Chiho Choi, Chen Sun
(* equal contribution)
WACV, 2024
project   paper

Ordered Atomic Activity for Fine-Grained Interactive Traffic Scenario Understanding
Nakul Agarwal, Yi-Ting Chen
ICCV, 2023
project   paper

Weakly-Supervised Action Segmentation and Unseen Error Detection in Anomalous Instructional Videos
Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal, Behzad Dariush
ICCV, 2023
project   paper

Latency Matters: Real-Time Action Forecasting Transformer
Harshayu Girase, Nakul Agarwal, Chiho Choi, Karttikeya Mangalam
CVPR, 2023 (Highlight - Selection rate 2.6%)
project   paper

AdamsFormer for Spatial Action Localization in the Future
Hyung-gun Chi, Kwonjoon Lee, Nakul Agarwal, Yi Xu, Karthik Ramani, Chiho Choi
CVPR, 2023
project   paper

Risk Perception in Driving Scenes
Nakul Agarwal, Yi-Ting Chen
Machine Learning for Autonomous Driving
NeurIPS, 2022
project   paper

Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos
Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal, Chiho Choi, Behzad Dariush
CVPR, 2022
project   paper

Unsupervised Domain Adaptation for Spatio-Temporal Action Localization
Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang
BMVC, 2020
project   paper

Short Version: VL3 Workshop, CVPR, 2020

SegRPN: Scale Aware Joint Object Detection and Semantic Segmentation
Nakul Agarwal, Wei-Chih Hung, Yi-Hsuan Tsai, Ming-Hsuan Yang
Manuscript, 2019
paper

Improving Multiclass Classification by Deep Networks using DAGSVM and Triplet Loss
Nakul Agarwal, Vineeth N. Balasubramaniam, C. V. Jawahar
Pattern Recognition Letters, 2018
paper   bibtex

Connecting Visual Experiences using Max-flow Network with Application to Visual Localization
Nakul Agarwal*, A.H. Abdul Hafez*, C. V. Jawahar
(* equal contribution)
arXiv, 2018
paper   bibtex

Course Projects

Exploring Action Recognition without using Deep Learning
Nakul Agarwal, 2019
report

Content Based Image Retrieval
Nakul Agarwal, 2018
report

Simultaneous Localization and Mapping using Extended Kalmann Filter
Nakul Agarwal, Aditya Ranganath, 2017
report

Teaching

Software Engineering (CSE 120), UC Merced
Teaching Assistant (TA) with Chi Yan Leung
Fall 2017

Computer Architecture (CSE 140), UC Merced
Teaching Assistant (TA) with Chi Yan Leung
Spring 2018

Intro to Digital Image Processing (CSE 107), UC Merced
Teaching Assistant (TA) with Shawn Newsam
Fall 2018



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