Ayan Chakrabarti

I'm an Assistant Professor in CSE at Washington University in St. Louis, where I direct the Vision & Learning Group. My research interests are in computer vision, machine learning, and computational photography.

I received my PhD from the School of Engineering and Applied Sciences at Harvard University in 2011, where my advisor was Todd Zickler. 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 also hold an SM degree in Engineering Sciences from Harvard (2008), and BTech and MTech degrees in Electrical Engineering from IIT Madras (2006).

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research

Basis Prediction Networks for Effective Burst Denoising with Large Kernels

arXiv 2019

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

paper  

Generating and Exploiting Probabilistic Monocular Depth Estimates

arXiv 2019

Zhihao Xia, Patrick Sullivan, Ayan Chakrabarti

paper  

Protecting Geolocation Privacy of Photo Collections

AAAI 2020

Jinghan Yang, Ayan Chakrabarti, Yevgeniy Vorobeychik

paper   project  

Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures

WACV 2020

Kyle Yee, Ayan Chakrabarti

paper   project  

Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising

WACV 2020

Zhihao Xia, Ayan Chakrabarti

paper   project  

Training Image Estimators without Image Ground-Truth

NeurIPS 2019 (spotlight)

Zhihao Xia, Ayan Chakrabarti

paper   project  

Backprop with Approximate Activations for Memory-efficient Network Training

NeurIPS 2019

Ayan Chakrabarti, Benjamin Moseley

paper   project  

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

ICCAD 2019

Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang

paper  

Learning to Separate Multiple Illuminants in a Single Image

CVPR 2019

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

paper   project  

Jointly Learning to Construct and Control Agents using Deep Re­infor­cement Learning

ICRA 2019

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

paper   project  

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  

Learning Privacy Preserving Encodings through Adv­er­sarial Training

WACV 2019

Francesco Pittaluga, Sanjeev J. Koppal, Ayan Chakrabarti

paper  

Stabilizing GAN Training with Multiple Random Projections

arXiv 2018

Behnam Neyshabur, Srinadh Bhojanapalli, Ayan Chakrabarti

paper   project  

Jointly Optimizing Placement and Inference for Beacon-based Localization

IROS 2017

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

paper   project  

Examining the Impact of Blur on Recognition by Conv­olut­ional Networks

arXiv 2017

Igor Vasiljevic, Ayan Chakrabarti, Gregory Shakhnarovich

paper  

Learning Sensor Multiplexing Design through Back-propagation

NeurIPS 2016

Ayan Chakrabarti

paper   project  

Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

NeurIPS 2016

Ayan Chakrabarti, Jingyu Shao, Gregory Shakhnarovich

paper   project  

Single-image RGB Photometric Stereo With Spatially-varying Albedo

3DV 2016 (oral)

Ayan Chakrabarti, Kalyan Sunkavalli

paper   project  

A Neural Approach to Blind Motion Deblurring

ECCV 2016

Ayan Chakrabarti

paper   project  

Color Constancy by Learning to Predict Chromaticity from Luminance

NeurIPS 2015 (spotlight)

Ayan Chakrabarti

paper   project  

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

CVPR 2015

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

paper   project  

From Shading to Local Shape

PAMI 2015

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

paper   project  

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  

Rethinking Color Cameras

ICCP 2014

Ayan Chakrabarti, William T. Freeman, Todd Zickler

paper   project  

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

ECCV 2012

Ayan Chakrabarti, Todd Zickler

paper   project   video  

Color Constancy with Spatio-Spectral Statistics

PAMI 2012

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper   project  

Statistics of Real-World Hyperspectral Images

CVPR 2011

Ayan Chakrabarti, Todd Zickler

paper   project  

Learning Object Color Models from Multi-view Constraints

CVPR 2011

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

paper  

Analyzing Spatially-varying Blur

CVPR 2010

Ayan Chakrabarti, Todd Zickler, William T. Freeman

paper   project  

An Empirical Camera Model for Internet Color Vision

BMVC 2009

Ayan Chakrabarti, Daniel Scharstein, Todd Zickler

paper   project  

Color Constancy Beyond Bags of Pixels

CVPR 2008

Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler

paper  

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

ICASSP 2008

Ayan Chakrabarti, Keigo Hirakawa

paper  

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

IEEE Transactions on Multimedia 2007

Ayan Chakrabarti, A.N. Rajagopalan, Rama Chellappa

paper  

Visual Inference with Statistical Models for Color and Texture

Ph.D. Dissertation, Harvard University, 2011

Ayan Chakrabarti

pdf  

Copyright © 2020, Ayan Chakrabarti.