Aayush Bansal

I received a PhD in Robotics from Carnegie Mellon University for my work on unsupervised learning of the 4D audio-visual world from sparse unconstrained real-world samples. I am really fortunate to have spent the wonderful graduate school days under the tutelage of Deva Ramanan and Yaser Sheikh. During the course of my graduate studies, I received an Uber Presidential Fellowship for 2016-17 and was named a Presidential Fellow at CMU, a Qualcomm Fellowship for 2017-18, and a Snap Fellowship for 2019. I am also fortunate to have collaborated with many production houses in the last few years. I have also spent time as a researcher at Meta's Reality Labs Research (Pittsburgh) in amazing Yaser Sheikh's group.

Email / CV / Google Scholar / GitHub / Thesis Talk

Academic Service

Area Chair : CVPR 2025, CVPR 2024.
Reviewer : CVPR (outstanding reviewer x2), ECCV (outstanding reviewer x1), ICCV, NeurIPS (outstanding reviewer x1), ICLR, ICML, SIGGRAPH, TPAMI, IJCV, TOG.

Research

My goal is to build artificial intelligence based on task-and-domain-agnostic exemplar representations learned in an unsupervised manner.

VR-NeRF: High-Fidelity Virtualized Walkable Spaces
Linning Xu, Vasu Agrawal,William Laney, Tony Garcia, Aayush Bansal,
Changil Kim, Samuel Rota Bulo, Lorenzo Porzi, Peter Kontschieder,
Aljaz Bozic, Dahua Lin, Michael Zollhoefer, Christian Richardt
SIGGRAPH Asia (Conference), 2023
project page / arXiv

EgoHumans: An Egocentric 3D Multi-Human Benchmark
Rawal Khirodkar, Aayush Bansal, Lingni Ma, Richard Newcombe,
Minh Vo, Kris Kitani
International Conference on Computer Vision (ICCV), 2023
(Oral Presentation), EgoVis 2022/2023 Distinguished Paper Award
project page / arXiv

Neural Pixel Composition for
3D-4D View Synthesis from Multi-Views
Aayush Bansal, Michael Zollhoefer
Computer Vision and Pattern Recognition (CVPR), 2023
project page / paper [100 MB]

KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints
Marko Mihajlovic, Aayush Bansal, Michael Zollhoefer,
Siyu Tang, Shunsuke Saito
European Conference on Computer Vision (ECCV), 2022
project page / paper / summary / code

COAP: Compositional Articulated Occupancy of People
Marko Mihajlovic, Shunsuke Saito, Aayush Bansal,
Michael Zollhoefer, Siyu Tang
Computer Vision and Pattern Recognition (CVPR), 2022
project page / paper / summary / code

Video-Specific Autoencoders for
Exploring, Editing and Transmitting Videos
Kevin Wang, Deva Ramanan, Aayush Bansal

project page / paper / summary / code

Unsupervised Audiovisual Synthesis via Exemplar Autoencoders
Kangle Deng, Aayush Bansal, Deva Ramanan
International Conference on Learning Representations (ICLR), 2021
project page / paper / open-review / code

Streaming Self-Training via
Domain-Agnostic Unlabeled Images
Zhiqiu Lin, Deva Ramanan, Aayush Bansal

project page / paper / arXiv

Stereo Radiance Fields:
Learning View Synthesis for Sparse Views of Novel Scenes
Julian Chibane, Aayush Bansal, Verica Lazova, Gerard Pons-Moll
Computer Vision and Pattern Recognition (CVPR), 2021
project page / paper / code

4D Visualization of Dynamic Events from
Unconstrained Multi-View Videos
Aayush Bansal, Minh Vo, Yaser Sheikh, Deva Ramanan, Srinivasa Narasimhan
Computer Vision and Pattern Recognition (CVPR), 2020
project page / paper / arXiv /summary / multi-view sequences
CMU Press Coverage

Shapes and Context : In-the-wild Image Synthesis & Manipulation
Aayush Bansal, Yaser Sheikh, Deva Ramanan
Computer Vision and Pattern Recognition (CVPR), 2019
(Oral Presentation, Best Paper Award Finalist)
project page / paper / arXiv / five minutes / CVPR Talk
web-app (beta version) / code / demo video

Recycle-GAN: Unsupervised Video Retargeting
Aayush Bansal, Shugao Ma, Deva Ramanan, Yaser Sheikh
European Conference on Computer Vision (ECCV), 2018
project page / pre-print / arXiv / code / one minute
CMU Press Coverage

PixelNN: Example-based Image Synthesis
Aayush Bansal, Yaser Sheikh, Deva Ramanan
International Conference on Learning Representations (ICLR), 2018
project page / arXiv / paper / codes

PixelNet: Representation of the pixels, by the pixels, and for the pixels.
Aayush Bansal, Xinlei Chen, Bryan Russell, Abhinav Gupta, Deva Ramanan
project page / arXiv / codes

Marr Revisited: 2D-3D Alignment via Surface Normal Prediction
Aayush Bansal, Bryan Russell, Abhinav Gupta
Computer Vision and Pattern Recognition (CVPR), 2016
project page /arXiv preprint / codes

	Patch Correspondences for Intepreting Pixel-level CNNs Victor Fragoso, Chunhui Liu, Aayush Bansal, Deva Ramanan arXiv
	Mid-level Elements for Object Detection Aayush Bansal, Abhinav Shrivastava, Carl Doersch, Abhinav Gupta arXiv / analysis
	Towards Transparent Systems: Semantic Characterization of Failure Modes Aayush Bansal, Ali Farhadi, Devi Parikh European Conference on Computer Vision (ECCV), 2014 project page / supplementary material VT NEWS / Virginia Center for Autonomous Systems
	Understanding How Camera Configuration and Environmental Conditions Affect Appearance-based Localization Aayush Bansal, Hernan Badino, Daniel Huber IEEE Intelligent Vehicles (IV), 2014 project page
	Which Edges Matter? Aayush Bansal, Adarsh Kowdle, Devi Parikh, Andrew Gallagher, Larry Zitnick Workshop on 3D Representation and Recognition (3dRR) at ICCV, 2013 project page / presentation
	CANINE : A robotic mine dog B. A. Stancil, J. Hyams, J. Shelly, K. Babu, H. Badino, A. Bansal, D. Huber, P. Batavia IS&T Conference on Electronic Imaging (SPIE), 2013 project page / video / competition rules I wrote the object detection module for this robot.

New Art Display

Teaching

Geometry-based Methods in Computer Vision (16-822), CMU
Teaching Assistant (TA) with Prof Martial Hebert
Fall 2017

Computer Vision (16-720), CMU
Teaching Assistant (TA) with Prof Srinivasa Narasimhan
Spring 2015