Ayan Chakrabarti

I am a Research Scientist at Google research in New York. I am interested in problems in machine learning, computer vision, and computational photography.

I received my PhD advised by Todd Zickler at Harvard University, and did my undergraduate studies at IIT Madras. Before joining Google, I was an assistant professor of computer science at WashU, a research assistant professor at the Toyota Technological Institute at Chicago, and a post-doctoral fellow at Harvard.

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Ayan Chakrabarti

Research Scientist, Google

Google Scholar / GitHub / CV / E-mail

Research

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Leveraging Redundancy in Attention with Reuse Transformers

arXiv 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar

paper

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Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation

arXiv 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit

paper

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Understanding Robustness of Transformers for Image Classification

ICCV 2021

Srinadh Bhojanapalli, Ayan Chakrabarti, Daniel Glasner, Daliang Li, Thomas Unterthiner, Andreas Veit

paper

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Can Optical Trojans Assist Adversarial Perturbations?

AROW (ICCV) 2021

Adith Boloor, Tong Wu, Patrick Naughton, Ayan Chakrabarti, Xuan Zhang, Yevgeniy Vorobeychik

paper

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Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments

CVPR 2021

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

paper project

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Real-Time Edge Classification: Optimal Offloading under Token Bucket Constraints

SEC 2021

Ayan Chakrabarti, Roch Guérin, Chenyang Lu, Jiangnan Liu

arxiv code

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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, Michaël 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

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