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07/20/2023
Physics-Driven Turbulence Image Restoration with Stochastic Refinement
Image distortion by atmospheric turbulence is a stochastic degradation, ...
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06/30/2023
Spatially Varying Exposure with 2-by-2 Multiplexing: Optimality and Universality
The advancement of new digital image sensors has enabled the design of e...
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03/30/2023
HDR Imaging with Spatially Varying Signal-to-Noise Ratios
While today's high dynamic range (HDR) image fusion algorithms are capab...
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03/29/2023
Towards Understanding the Effect of Pretraining Label Granularity
In this paper, we study how pretraining label granularity affects the ge...
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07/20/2022
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model
Image restoration algorithms for atmospheric turbulence are known to be ...
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07/13/2022
Imaging through the Atmosphere using Turbulence Mitigation Transformer
Restoring images distorted by atmospheric turbulence is a long-standing ...
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11/09/2021
Graph-Based Depth Denoising Dequantization for Point Cloud Enhancement
A 3D point cloud is typically constructed from depth measurements acquir...
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08/20/2021
Detecting and Segmenting Adversarial Graphics Patterns from Images
Adversarial attacks pose a substantial threat to computer vision system ...
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08/13/2021
Optical Adversarial Attack
We introduce OPtical ADversarial attack (OPAD). OPAD is an adversarial a...
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07/24/2021
Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform
Fast and accurate simulation of imaging through atmospheric turbulence i...
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06/30/2021
Graph Signal Restoration Using Nested Deep Algorithm Unrolling
Graph signal processing is a ubiquitous task in many applications such a...
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06/24/2021
Driver-centric Risk Object Identification
A massive number of traffic fatalities are due to driver errors. To redu...
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03/13/2021
Student-Teacher Learning from Clean Inputs to Noisy Inputs
Feature-based student-teacher learning, a training method that encourage...
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11/06/2020
HDR Imaging with Quanta Image Sensors: Theoretical Limits and Optimal Reconstruction
High dynamic range (HDR) imaging is one of the biggest achievements in m...
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07/16/2020
Dynamic Low-light Imaging with Quanta Image Sensors
Imaging in low light is difficult because the number of photons arriving...
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06/03/2020
Image Classification in the Dark using Quanta Image Sensors
State-of-the-art image classifiers are trained and tested using well-ill...
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05/19/2020
One Size Fits All: Can We Train One Denoiser for All Noise Levels?
When training an estimator such as a neural network for tasks like image...
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04/23/2020
Simulating Anisoplanatic Turbulence by Sampling Inter-modal and Spatially Correlated Zernike Coefficients
Simulating atmospheric turbulence is an essential task for evaluating tu...
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03/05/2020
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference
We propose a framework based on causal inference for risk object identif...
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09/20/2019
Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks
To enable intelligent automated driving systems, a promising strategy is...
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05/17/2019
Rethinking Atmospheric Turbulence Mitigation
State-of-the-art atmospheric turbulence image restoration methods utiliz...
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03/23/2019
Color Filter Arrays for Quanta Image Sensors
Quanta image sensor (QIS) is to be the next generation image sensor afte...
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08/31/2018
Performance Analysis of Plug-and-Play ADMM: A Graph Signal Processing Perspective
The Plug-and-Play (PnP) ADMM algorithm is a powerful image restoration f...
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08/24/2018
Automatic Foreground Extraction using Multi-Agent Consensus Equilibrium
While foreground extraction is fundamental to virtual reality systems an...
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11/17/2017
Integrating Disparate Sources of Experts for Robust Image Denoising
We study an image denoising problem: Given a set of image denoisers, eac...
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02/01/2016
Algorithm-Induced Prior for Image Restoration
This paper studies a type of image priors that are constructed implicitl...
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01/19/2016
Adaptive Image Denoising by Mixture Adaptation
We propose an adaptive learning procedure to learn patch-based image pri...
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01/01/2016
Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective
Many patch-based image denoising algorithms can be formulated as applyin...
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07/14/2014
Depth Reconstruction from Sparse Samples: Representation, Algorithm, and Sampling
The rapid development of 3D technology and computer vision applications ...
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06/30/2014
Adaptive Image Denoising by Targeted Databases
We propose a data-dependent denoising procedure to restore noisy images....
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12/27/2013