activity
20182020
most citedDeep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CV2020

A Dark Flash Normal Camera

Zhihao Xia, Jason Lawrence, Supreeth Achar

Casual photography is often performed in uncontrolled lighting that can result in low quality images and degrade the performance of downstream processing. We consider the problem o…

cs.CV20201 cited

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

Zhihao Xia, Michaël Gharbi, Federico Perazzi +2

We introduce a neural network-based method to denoise pairs of images taken in quick succession, with and without a flash, in low-light environments. Our goal is to produce a high-…

cs.CV2019

Basis Prediction Networks for Effective Burst Denoising with Large Kernels

Zhihao Xia, Federico Perazzi, Michaël Gharbi +2

Bursts of images exhibit significant self-similarity across both time and space. This motivates a representation of the kernels as linear combinations of a small set of basis eleme…

cs.CV2019

Training Image Estimators without Image Ground-Truth

Zhihao Xia, Ayan Chakrabarti

Deep neural networks have been very successful in image estimation applications such as compressive-sensing and image restoration, as a means to estimate images from partial, blurr…

cs.CV2019

Generating and Exploiting Probabilistic Monocular Depth Estimates

Zhihao Xia, Patrick Sullivan, Ayan Chakrabarti

Beyond depth estimation from a single image, the monocular cue is useful in a broader range of depth inference applications and settings---such as when one can leverage other avail…

cs.CV2018

Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising

Zhihao Xia, Ayan Chakrabarti

Image denoising methods must effectively model, implicitly or explicitly, the vast diversity of patterns and textures that occur in natural images. This is challenging, even for mo…