activity
20182022
most citedTransposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

6 citations · 10 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV2022

HIME: Efficient Headshot Image Super-Resolution with Multiple Exemplars

Xiaoyu Xiang, Jon Morton, Fitsum A Reda +6

A promising direction for recovering the lost information in low-resolution headshot images is utilizing a set of high-resolution exemplars from the same identity. Complementary im…

eess.IV2021

Feature-Align Network with Knowledge Distillation for Efficient Denoising

Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan +6

We propose an efficient neural network for RAW image denoising. Although neural network-based denoising has been extensively studied for image restoration, little attention has bee…

cs.CV2020

EVRNet: Efficient Video Restoration on Edge Devices

Sachin Mehta, Amit Kumar, Fitsum Reda +4

Video transmission applications (e.g., conferencing) are gaining momentum, especially in times of global health pandemic. Video signals are transmitted over lossy channels, resulti…

cs.CV20206 cited

Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

Guilin Liu, Rohan Taori, Ting-Chun Wang +6

Conventional CNNs for texture synthesis consist of a sequence of (de)-convolution and up/down-sampling layers, where each layer operates locally and lacks the ability to capture th…

cs.CV20194 cited

Neural ODEs for Image Segmentation with Level Sets

Rafael Valle, Fitsum Reda, Mohammad Shoeybi +3

We propose a novel approach for image segmentation that combines Neural Ordinary Differential Equations (NODEs) and the Level Set method. Our approach parametrizes the evolution of…

cs.CV2019

Unsupervised Video Interpolation Using Cycle Consistency

Fitsum A. Reda, Deqing Sun, Aysegul Dundar +6

Learning to synthesize high frame rate videos via interpolation requires large quantities of high frame rate training videos, which, however, are scarce, especially at high resolut…