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05/26/2023
High-Fidelity Image Compression with Score-based Generative Models
Despite the tremendous success of diffusion generative models in text-to...
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04/14/2023
M2T: Masking Transformers Twice for Faster Decoding
We show how bidirectional transformers trained for masked token predicti...
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12/28/2022
Multi-Realism Image Compression with a Conditional Generator
By optimizing the rate-distortion-realism trade-off, generative compress...
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06/15/2022
VCT: A Video Compression Transformer
We show how transformers can be used to vastly simplify neural video com...
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07/26/2021
Towards Generative Video Compression
We present a neural video compression method based on generative adversa...
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02/18/2021
On the advantages of stochastic encoders
Stochastic encoders have been used in rate-distortion theory and neural ...
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07/06/2020
Nonlinear Transform Coding
We review a class of methods that can be collected under the name nonlin...
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06/17/2020
High-Fidelity Generative Image Compression
We extensively study how to combine Generative Adversarial Networks and ...
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06/17/2020
Universally Quantized Neural Compression
A popular approach to learning encoders for lossy compression is to use ...
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12/05/2018
Interactive Full Image Segmentation
We address the task of interactive full image annotation, where the goal...
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11/30/2018
Practical Full Resolution Learned Lossless Image Compression
We propose the first practical learned lossless image compression system...
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10/03/2018
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
This paper reviews the first challenge on efficient perceptual image enh...
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05/28/2018
Deep Generative Models for Distribution-Preserving Lossy Compression
We propose and study the problem of distribution-preserving lossy compre...
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04/09/2018
Generative Adversarial Networks for Extreme Learned Image Compression
We propose a framework for extreme learned image compression based on Ge...
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03/16/2018
Towards Image Understanding from Deep Compression without Decoding
Motivated by recent work on deep neural network (DNN)-based image compre...
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01/12/2018
Conditional Probability Models for Deep Image Compression
Deep Neural Networks trained as image auto-encoders have recently emerge...
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12/19/2017
ComboGAN: Unrestrained Scalability for Image Domain Translation
This year alone has seen unprecedented leaps in the area of learning-bas...
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12/12/2017
Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks
Designing a logo for a new brand is a lengthy and tedious back-and-forth...
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11/06/2017
Optimal transport maps for distribution preserving operations on latent spaces of Generative Models
Generative models such as Variational Auto Encoders (VAEs) and Generativ...
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08/09/2017
WebVision Database: Visual Learning and Understanding from Web Data
In this paper, we present a study on learning visual recognition models ...
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05/16/2017
WebVision Challenge: Visual Learning and Understanding With Web Data
We present the 2017 WebVision Challenge, a public image recognition chal...
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04/03/2017
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
We present a new approach to learn compressible representations in deep ...
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05/30/2016
k2-means for fast and accurate large scale clustering
We propose k^2-means, a new clustering method which efficiently copes wi...
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03/13/2014
