Ayan Chakrabarti

I'm an Assistant Professor in the CSE department at WashU, where I direct the Vision & Learning Group. I work on research problems in computer vision, machine learning, and computational photography.

I received my PhD in 2011 advised by Todd Zickler at Harvard University. I was a post-doctoral fellow at Harvard from 2011-2014, and a research assistant professor at the Toyota Technological institute at Chicago from 2014-2017. I did my undergraduate studies at IIT Madras, receiving BTech and MTech degrees in Electrical Engineering in 2006.

GScholar | GitHub | CV | E-mail

research

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Generating and Exploiting Probabilistic Monocular Depth Estimates

CVPR 2020 oral

Zhihao Xia, Patrick Sullivan, Ayan Chakrabarti

paper project

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Basis Prediction Networks for Effective Burst Denoising with Large Kernels

CVPR 2020

Zhihao Xia, Federico Perazzi, Michaƫl Gharbi, Kalyan Sunkavalli, Ayan Chakrabarti

paper project

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Protecting Geolocation Privacy of Photo Collections

AAAI 2020

Jinghan Yang, Ayan Chakrabarti, Yevgeniy Vorobeychik

paper project

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Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures

WACV 2020

Kyle Yee, Ayan Chakrabarti

paper project

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Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising

WACV 2020

Zhihao Xia, Ayan Chakrabarti

paper project

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Training Image Estimators without Image Ground-Truth

NeurIPS 2019 spotlight

Zhihao Xia, Ayan Chakrabarti

paper project

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Backprop with Approximate Activations for Memory-efficient Network Training

NeurIPS 2019

Ayan Chakrabarti, Benjamin Moseley

paper project

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Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices

ICCAD 2019 + TCAD

Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang

ICCAD TCAD

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Learning to Separate Multiple Illuminants in a Single Image

CVPR 2019

Zhuo Hui, Ayan Chakrabarti, Kalyan Sunkavalli, Aswin C. Sankaranarayanan

paper project

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Jointly Learning to Construct and Control Agents using Deep Re­infor­cement Learning

ICRA 2019

Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter

paper project

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NeuADC: Neural Network-Inspired RRAM-Based Syn­the­siz­able Analog-to-Digital Conversion with Re­conf­igur­able Quantization Support

DATE 2019 + TCAD

Weidong Cao, Xin He, Ayan Chakrabarti, Xuan Zhang

DATE TCAD

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Learning Privacy Preserving Encodings through Adv­er­sarial Training

WACV 2019

Francesco Pittaluga, Sanjeev J. Koppal, Ayan Chakrabarti

paper

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Stabilizing GAN Training with Multiple Random Projections

arXiv 2018

Behnam Neyshabur, Srinadh Bhojanapalli, Ayan Chakrabarti

paper project

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Jointly Optimizing Placement and Inference for Beacon-based Localization

IROS 2017

Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter

paper project

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Examining the Impact of Blur on Recognition by Conv­olut­ional Networks

arXiv 2017

Igor Vasiljevic, Ayan Chakrabarti, Gregory Shakhnarovich

paper

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Learning Sensor Multiplexing Design through Back-propagation

NeurIPS 2016

Ayan Chakrabarti

paper project

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Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

NeurIPS 2016

Ayan Chakrabarti, Jingyu Shao, Gregory Shakhnarovich

paper project

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Single-image RGB Photometric Stereo With Spatially-varying Albedo

3DV 2016 oral

Ayan Chakrabarti, Kalyan Sunkavalli

paper project

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A Neural Approach to Blind Motion Deblurring

ECCV 2016

Ayan Chakrabarti

paper project

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Color Constancy by Learning to Predict Chromaticity from Luminance

NeurIPS 2015 spotlight

Ayan Chakrabarti

paper project

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Low-level Vision by Consensus in a Spatial Hierarchy of Regions

CVPR 2015

Ayan Chakrabarti, Ying Xiong, Steven J. Gortler, Todd Zickler

paper project

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From Shading to Local Shape

PAMI 2015

Ying Xiong, Ayan Chakrabarti, Ronen Basri, Steven J. Gortler, David W. Jacobs, Todd Zickler

paper project

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Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images

PAMI 2014

Ayan Chakrabarti, Ying Xiong, Baochen Sun, Trevor Darrell, Daniel Scharstein, Todd Zickler, Kate Saenko

paper project

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Rethinking Color Cameras

ICCP 2014

Ayan Chakrabarti, William T. Freeman, Todd Zickler

paper project

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Depth and Deblurring from a Spectrally-varying Depth-of-Field

ECCV 2012

Ayan Chakrabarti, Todd Zickler

paper project video

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Color Constancy with Spatio-Spectral Statistics

PAMI 2012

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper project

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Statistics of Real-World Hyperspectral Images

CVPR 2011

Ayan Chakrabarti, Todd Zickler

paper project

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Learning Object Color Models from Multi-view Constraints

CVPR 2011

Trevor Owens, Kate Saenko, Ayan Chakrabarti, Ying Xiong, Todd Zickler, Trevor Darrell

paper

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Analyzing Spatially-varying Blur

CVPR 2010

Ayan Chakrabarti, Todd Zickler, William T. Freeman

paper project

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An Empirical Camera Model for Internet Color Vision

BMVC 2009

Ayan Chakrabarti, Daniel Scharstein, Todd Zickler

paper project

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Color Constancy Beyond Bags of Pixels

CVPR 2008

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper

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Effective Separation of Sparse and Non-sparse Image Features for Denoising

ICASSP 2008

Ayan Chakrabarti, Keigo Hirakawa

paper

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Super-Resolution of Face Images Using Kernel PCA-Based Prior

IEEE Transactions on Multimedia 2007

Ayan Chakrabarti, A.N. Rajagopalan, Rama Chellappa

paper

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Visual Inference with Statistical Models for Color and Texture

Ph.D. Dissertation, Harvard University, 2011

Ayan Chakrabarti

pdf

teaching

WUSTL CSE 559A Computer Vision
(Fall 17, 18, 19, 20)
WUSTL CSE 659A Advances in Computer Vision
(Spring  19, 20)

service

Program Chair & Organizer ICCP 2020 (+ Guest Editor PAMI special section)
Area Chair CVPR 2021  ECCV 2020  ICCV 2019  CVPR 2018  3DV 2017
Copyright © 2020, Ayan Chakrabarti.