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Viraj Shah
Viraj Shah

Viraj Shah

Research Scientist, Google

I am Research Scientist at Google in Computational Imaging team. Previously, I earned PhD from UIUC where I worked with Dr. Svetlana Lazebnik on Generative Models and Computer Vision.
RESUME GOOGLE SCHOLAR EMAIL PROJECTS

I am Viraj, Research Scientist at Google in Computational Imaging team. I obtained my PhD in Electrical Engineering at University of Illinois, Urbana-Champaign where I worked with Dr. Svetlana Lazebnik on Generative Models.

My research interests lie at the intersection of Computer Vision and Imaging Inverse Problems. I work on developing algorithms to leverage novel Generative Models and Deep Learning techniques in solving imaging and image manipulation problems. Please check out the Projects and Publications section, or my resume to learn more!

Previously, I completed B.Tech. in EE from IIT Roorkee in 2016 and joined PhD program at Iowa State University where I earned MS in ECE before transferring to UIUC. At DICE Lab, ISU, I worked under the guidance of Dr. Chinmay Hegde.

Throughout the course of my studies, I have had the privilege of working with and receiving guidance from amazing researchers and teams:

Projects & Publications


Generative Models

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Accepted to ECCV 2024!

ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAs

Viraj Shah, Nataniel Ruiz, Forrester Cole, Erika Lu, Svetlana Lazebnik, Yuanzhen Li, Varun Jampani
ECCV, 2024
paper | project page

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Best Paper Award at CVFAD Workshop, CVPR 2024!

Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Images

Aiyu Cui, Jay Mahajan, Viraj Shah, Preeti Gomathinayagam, Svetlana Lazebnik
WACV 2025
CVFAD Workshop, CVPR, 2024
paper | project page | video | poster

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MultiStyleGAN: Multiple One-shot Image Stylizations using a Single GAN

Viraj Shah, Ayush Sarkar, Sudharsan Krishna, Svetlana Lazebnik
paper | project page | code

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Generative AI: Challenges and Opportunities in the Context of India

Viraj Shah, Kartik Patel
EC3V Workshop, CVPR, 2023
paper | poster

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Make It So: Steering StyleGAN for Any Image Inversion and Editing

Anand Bhattad, Viraj Shah, Derek Hoiem, David A. Forsyth
paper | project page

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Near Perfect GAN Inversion

Qianli Feng, Viraj Shah, Raghudeep Gadde, Pietro Perona, Aleix Martinez
paper | slides

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Encoding Invariances in Deep Generative Models

Viraj Shah*, Ameya Joshi*, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde
paper

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InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models

Ameya Joshi, Minsu Cho, Viraj Shah, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde
AAAI, 2019
paper | code

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Generative Models for Solving Nonlinear Partial Differential Equations

Ameya Joshi*, Viraj Shah*, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde
MLPS Workshop, NeurIPS, 2019
paper

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Second Prize at MRS Open Data Challenge 2019!

Physics-aware Deep Generative Models for Creating Synthetic Microstructures

Rahul Singh*, Viraj Shah*, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde
MMLS Workshop, NeurIPS, 2018
paper | poster | slides | news


Imaging Inverse Problems

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Sparse Signal Recovery from Modulo Observations

Viraj Shah, Chinmay Hegde
EURASIP Journal on Advances in Signal Processing, 2020
paper | code | slides

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Signal Reconstruction from Modulo Observations

Viraj Shah, Chinmay Hegde
GlobalSIP, 2019
paper | code | slides

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Alternating Phase Projected Gradient Descent with Generative Priors for Solving Compressive Phase Retrieval

Rakib Hyder, Viraj Shah, Chinmay Hegde, Salman Asif
ICASSP, 2019
paper | code | poster

Extends the projected gradient descent-based approach to leverage Generative Priors for phase retrieval.

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Solving Linear Inverse Problems using GAN Priors: an Algorithm with Provable Guarantees

Viraj Shah, Chinmay Hegde
ICASSP, 2018
paper | code | poster | slides

Proposes a provable projected gradient descent-based approach to leverage Generative Priors for compressive sensing.

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Reconstruction from Periodic Non-linearities, with Applications to HDR Imaging

Viraj Shah, Mohammadreza Soltani, Chinmay Hegde
Asilomar, 2017
paper | poster

Reconstructing HDR image from multiple modulo images in compressive sensing setting.


Miscellaneous

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CloudFindr: A Deep Learning Cloud Artifact Masker for Satellite DEM Data

Kalina Borkiewicz, Viraj Shah, JP Naiman, Chuanyue Shen, Stuart Levy, Jeff Carpenter
VIS, 2021
paper

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Quantifying driver speed behavior from real-time physiology in type 1 diabetes

Viraj Shah, Jennifer Merickel, Pranamesh Charkraborty, Anuj Sharma, Chinmay Hegde,..., Matt Rizzo
Fast-ZERO, 2019
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