Rahul Venkatesh

I am a fourth year CS PhD student at Stanford advised by Prof. Dan Yamins. Previously, I graduated from CMU with a Master's in Computer Vision where I was advised by Prof. Laszlo Jeni from the Robotics Institute and Dr. Maneesh Singh from Verisk AI. I also closely collaborated with Prof. Zico Kolter from the CS department at CMU. Prior to that, I was a research assistant at the Video Analytics Lab at the Indian Institute of Science, Bangalore, where I was advised by Prof. R Venkatesh Babu.

Email / Google Scholar / Resume

Research

World Modeling

Understanding Physical Dynamics with Counterfactual World Modeling
Rahul Venkatesh*, Honglin Chen*, Kevin Feigelis*, Daniel M. Bear, Khaled Jedoui, Klemen Kotar, Felix Binder, Wanhee Lee, Sherry Liu, Kevin A. Smith, Judith E. Fan, Daniel L. K. Yamins
ECCV, 2024

Segmentation

Unsupervised 3d scene representation learning via movable object inference
Honglin Chen, Rahul Venkateshstrong>, Yoni Friedman, Jiajun Wu, Joshua Tenenbaum, Daniel Yamins*, Daniel Bear*
ECCV(oral), 2022

3D Reconstruction

	Unsupervised 3d scene representation learning via movable object inference Honglin Chen, Wanhee Lee, Koven Hong-Xing Yu, Rahul Venkatesh, Joshua Tenenbaum, Daniel Bear, Jiajun Wu, Daniel Yamins TMLR, 2023
	Deep Implicit Surface Point Prediction Networks Rahul Venkatesh, Tejan Karmali, Sarthak Sharma, Aurobrata Ghosh, R. Venkatesh Babu, Laszlo Jeni, Maneesh Singh ICCV, 2021
	Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh, Laszlo Jeni, Maneesh Singh arXiv, 2020
	Appearance Consensus Driven Self-Supervised Human Mesh Recovery Jogendra Nath Kundu, Rakesh Mugalodi, Varun Jampani, Rahul Venkatesh, R Venkatesh Babu ECCV (oral), 2020

Adversarial Machine Learning

Semantic Adversarial Robustness with Differentiable Ray-Tracing
Rahul Venkatesh, Eric Wong, J Zico Kolter
DiffCVGP Workshop at NeurIPS, 2020

Object Pose Estimation

	Object pose estimation from monocular image using multi-view keypoint correspondence Rahul Venkatesh, Jogendra Nath Kundu, Aditya Ganeshan, R Venkatesh Babu Geometry Meets Deep Learning workshop at ECCV*, 2018
	iSPA-Net: Iterative Semantic Pose Alignment Network Rahul Venkatesh, Jogendra Nath Kundu, Aditya Ganeshan, Aditya Prakash, R Venkatesh Babu ACMMM*, 2018

Human Pose Estimation

	Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation Rahul Venkatesh, Jogendra Nath Kundu, Siddharth Seth, Rakesh Mugalodi, R Venkatesh Babu AAAI (oral)*, 2020
	Cross-Dataset Adaptation via Probabilistic Amodal 3D Human Pose Completion Rahul Venkatesh, Jogendra Nath Kundu, Jay Patravali, R Venkatesh Babu WACV*, 2020
	Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation Jogendra Nath Kundu* Revanur Ambareesh, Govind Vitthal Waghmare, Rahul Venkatesh, R Venkatesh Babu ECCV*, 2020
	Cross-Conditioned Recurrent Networks for Long-Term Synthesis of Inter-Person Human Motion Interactions Jogendra Nath Kundu, Himanshu Buckchash, Priyanka Mandikal, Anirudh Jamkhandi, Rahul Venkatesh, R Venkatesh Babu WACV, 2020

Unsupervised, Source-Free Domain Adaptation

	Class-Incremental Domain Adaptation Rahul Venkatesh, Jogendra Nath Kundu, Naveen Venkat, R Venkatesh Babu ECCV, 2020
	Universal Source-Free Domain Adaptation Jogendra Nath Kundu, Naveen Venkat, Rahul Venkatesh, R Venkatesh Babu CVPR, 2020
	Towards Inheritable Models for Open-Set Domain Adaptation Jogendra Nath Kundu, Naveen Venkat, Revanur Ambareesh, Rahul Venkatesh, R Venkatesh Babu CVPR (oral), 2020

Data-Efficient Object Tracking

Siamese network for underwater multiple object tracking
Rahul Venkatesh, Revanur Ambareesh, Shobha G
ICMLC (oral), Best Presentation Award, 2020

Traffic-flow Optimization

	An adaptive model for traffic flow optimisation in dynamic environments Rahul Venkatesh, Rajashree Shettar, KN Subramanya International Journal of Computational Science and Engineering, 2019
* => (Equal Contribution)

Source: Jon Barron -> template