CVPR 2020 (oral)
Generating and Exploiting Probabilistic Monocular Depth Estimates
Zhihao Xia, Patrick Sullivan, Ayan Chakrabarti
CVPR 2020
Basis Prediction Networks for Effective Burst Denoising with Large Kernels
Zhihao Xia, Federico Perazzi, Michaƫl Gharbi, Kalyan Sunkavalli, Ayan Chakrabarti
AAAI 2020
Protecting Geolocation Privacy of Photo Collections
Jinghan Yang, Ayan Chakrabarti, Yevgeniy Vorobeychik
WACV 2020
Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures
Kyle Yee, Ayan Chakrabarti
WACV 2020
Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising
Zhihao Xia, Ayan Chakrabarti
NeurIPS 2019 (spotlight)
Training Image Estimators without Image Ground-Truth
Zhihao Xia, Ayan Chakrabarti
NeurIPS 2019
Backprop with Approximate Activations for Memory-efficient Network Training
Ayan Chakrabarti, Benjamin Moseley
ICCAD 2019 + TCAD
Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices
Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang
CVPR 2019
Learning to Separate Multiple Illuminants in a Single Image
Zhuo Hui, Ayan Chakrabarti, Kalyan Sunkavalli, Aswin C. Sankaranarayanan
ICRA 2019
Jointly Learning to Construct and Control Agents using Deep Reinforcement Learning
Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter
DATE 2019 + TCAD
NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support
Weidong Cao, Xin He, Ayan Chakrabarti, Xuan Zhang
WACV 2019
Learning Privacy Preserving Encodings through Adversarial Training
Francesco Pittaluga, Sanjeev J. Koppal, Ayan Chakrabarti
arXiv 2018
Stabilizing GAN Training with Multiple Random Projections
Behnam Neyshabur, Srinadh Bhojanapalli, Ayan Chakrabarti
IROS 2017
Jointly Optimizing Placement and Inference for Beacon-based Localization
Charles Schaff, David Yunis, Ayan Chakrabarti, Matthew R. Walter
arXiv 2017
Examining the Impact of Blur on Recognition by Convolutional Networks
Igor Vasiljevic, Ayan Chakrabarti, Gregory Shakhnarovich
NeurIPS 2016
Learning Sensor Multiplexing Design through Back-propagation
Ayan Chakrabarti
NeurIPS 2016
Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions
Ayan Chakrabarti, Jingyu Shao, Gregory Shakhnarovich
3DV 2016 (oral)
Single-image RGB Photometric Stereo With Spatially-varying Albedo
Ayan Chakrabarti, Kalyan Sunkavalli
ECCV 2016
A Neural Approach to Blind Motion Deblurring
Ayan Chakrabarti
NeurIPS 2015 (spotlight)
Color Constancy by Learning to Predict Chromaticity from Luminance
Ayan Chakrabarti
CVPR 2015
Low-level Vision by Consensus in a Spatial Hierarchy of Regions
Ayan Chakrabarti, Ying Xiong, Steven J. Gortler, Todd Zickler
PAMI 2015
From Shading to Local Shape
Ying Xiong, Ayan Chakrabarti, Ronen Basri, Steven J. Gortler, David W. Jacobs, Todd Zickler
PAMI 2014
Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images
Ayan Chakrabarti, Ying Xiong, Baochen Sun, Trevor Darrell, Daniel Scharstein, Todd Zickler, Kate Saenko
ICCP 2014
Rethinking Color Cameras
Ayan Chakrabarti, William T. Freeman, Todd Zickler
ECCV 2012
Depth and Deblurring from a Spectrally-varying Depth-of-Field
Ayan Chakrabarti, Todd Zickler
Contact
Prof. Ayan Chakrabarti
Computer Science & Engineering
Washington University in St. Louis
1 Brookings Dr. CB #1045
St. Louis, MO 63130