Research
I am interested in developing robust computer vision systems that can understand the world around us.
Some areas of particular interest include 3D vision, distribution shifts and learning from unstructured visual data.
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Accidental Light Probes
Hong-Xing Yu, Samir Agarwala, Charles Herrmann,
Richard Szeliski, Noah Snavely, Jiajun Wu,
Deqing Sun
CVPR, 2023
project page /
arXiv
Specular objects such as coke cans often appear "accidentally" in images and can be used to recover scene lighting from single image observations using differentiable rendering.
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PlaneFormers: From Sparse View Planes to 3D Reconstruction
Samir Agarwala, Linyi Jin, Chris Rockwell,
David F. Fouhey
ECCV, 2022
project page /
arXiv
Transformers are really good at integrating evidence across multiple views and producing a planar reconstruction.
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Using Discrete-Event Simulation to Analyze the Impact of Variation on Surgical Training Programs
Fumiya Abe-Nornes, Samir Agarwala, Nathan Smith, Rachel Zhang, Amy Cohn,
Angela Thelen, Rishindra Reddy, Brian George
WSC, 2022
Paper
Real-life variation in learning speeds of surgical trainees and decrease in available training opportunities can
affect trainee competency and potentially endager patient safety.
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RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes
JT Walker*, DC Saunders*, V Rai*, C Dai, P Orchard, AL Hopkirk, CV Reihsmann, Y Tao, S Fan, S Shrestha,
A Varshney, JJ Wright, YD Pettway, C Ventresca, Samir Agarwala, R Aramandla, G Poffenberger, R Jenkins,
NJ Hart, DL Greiner, LD Shultz, R Bottino, Human Pancreas Analysis Program, J Liu, SCJ Parker*, AC Powers*,
M Brissova*
bioRxiv, 2021
bioRxiv
Identifying early disease-driving events of type 2 diabetes through integrative analysis of diverse modalities.
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