activity
20172021
most citedDeep Bilateral Learning for Real-Time Image Enhancement

832 citations · 838 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.CV2021

Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition

James Hong, Matthew Fisher, Michaël Gharbi +1

Human pose is a useful feature for fine-grained sports action understanding. However, pose estimators are often unreliable when run on sports video due to domain shift and factors…

cs.CV20211 cited

Modulated Periodic Activations for Generalizable Local Functional Representations

Ishit Mehta, Michaël Gharbi, Connelly Barnes +3

Multi-Layer Perceptrons (MLPs) make powerful functional representations for sampling and reconstruction problems involving low-dimensional signals like images,shapes and light fiel…

cs.CV2021

MarioNette: Self-Supervised Sprite Learning

Dmitriy Smirnov, Michael Gharbi, Matthew Fisher +3

Artists and video game designers often construct 2D animations using libraries of sprites -- textured patches of objects and characters. We propose a deep learning approach that de…

cs.CV20211 cited

Im2Vec: Synthesizing Vector Graphics without Vector Supervision

Pradyumna Reddy, Michael Gharbi, Michal Lukac +1

Vector graphics are widely used to represent fonts, logos, digital artworks, and graphic designs. But, while a vast body of work has focused on generative algorithms for raster ima…

cs.CV2020

Spatially-Adaptive Pixelwise Networks for Fast Image Translation

Tamar Rott Shaham, Michael Gharbi, Richard Zhang +2

We introduce a new generator architecture, aimed at fast and efficient high-resolution image-to-image translation. We design the generator to be an extremely lightweight function 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-…