b'Shuhang Gu'

research

∙ 03/31/2023

Single Image Depth Prediction Made Better: A Multivariate Gaussian Take

Neural-network-based single image depth prediction (SIDP) is a challengi...

0 Ce Liu, et al. ∙

research

∙ 02/13/2023

VA-DepthNet: A Variational Approach to Single Image Depth Prediction

We introduce VA-DepthNet, a simple, effective, and accurate deep neural ...

0 Ce Liu, et al. ∙

research

∙ 05/26/2022

Measuring Perceptual Color Differences of Smartphone Photography

Measuring perceptual color differences (CDs) is of great importance in m...

0 Zhihua Wang, et al. ∙

research

∙ 05/11/2022

Revisiting Random Channel Pruning for Neural Network Compression

Channel (or 3D filter) pruning serves as an effective way to accelerate ...

0 Yawei Li, et al. ∙

research

∙ 04/20/2022

NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results

In this paper, we summarize the 1st NTIRE challenge on stereo image supe...

7 Longguang Wang, et al. ∙

research

∙ 07/27/2021

MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN

Generative adversarial networks (GANs) have promoted remarkable advances...

0 Wenlong Cheng, et al. ∙

research

∙ 05/28/2021

Improving Facial Attribute Recognition by Group and Graph Learning

Exploiting the relationships between attributes is a key challenge for i...

6 Zhenghao Chen, et al. ∙

research

∙ 05/17/2021

Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report

Video super-resolution has recently become one of the most important mob...

35 Andrey Ignatov, et al. ∙

research

∙ 03/29/2021

Flow-based Kernel Prior with Application to Blind Super-Resolution

Kernel estimation is generally one of the key problems for blind image s...

0 Jingyun Liang, et al. ∙

research

∙ 09/14/2020

AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results

This paper reviews the video extreme super-resolution challenge associat...

9 Dario Fuoli, et al. ∙

research

∙ 09/13/2020

Improving Deep Video Compression by Resolution-adaptive Flow Coding

In the learning based video compression approaches, it is an essential i...

3 Zhihao Hu, et al. ∙

research

∙ 08/02/2020

Video Super-Resolution with Recurrent Structure-Detail Network

Most video super-resolution methods super-resolve a single reference fra...

0 Takashi Isobe, et al. ∙

research

∙ 06/30/2020

You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network

In this paper, we study two challenging and less-touched problems in sin...

0 Boyun Li, et al. ∙

research

∙ 06/29/2020

The Heterogeneity Hypothesis: Finding Layer-Wise Dissimilated Network Architecture

In this paper, we tackle the problem of convolutional neural network des...

8 Yawei Li, et al. ∙

research

∙ 05/13/2020

Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network

We propose the first practical multitask image enhancement network, that...

4 Dario Kneubuehler, et al. ∙

research

∙ 04/14/2020

Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning

Existing unsupervised video-to-video translation methods fail to produce...

8 Kangning Liu, et al. ∙

research

∙ 04/02/2020

Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training

These days, unsupervised super-resolution (SR) has been soaring due to i...

0 Yunxuan Wei, et al. ∙

research

∙ 03/30/2020

DHP: Differentiable Meta Pruning via HyperNetworks

Network pruning has been the driving force for the efficient inference o...

7 Yawei Li, et al. ∙

research

∙ 03/19/2020

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression

In this paper, we analyze two popular network compression techniques, i....

18 Yawei Li, et al. ∙

research

∙ 11/18/2019

AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results

This paper reviews the AIM 2019 challenge on real world super-resolution...

12 Andreas Lugmayr, et al. ∙

research

∙ 11/18/2019

Frequency Separation for Real-World Super-Resolution

Most of the recent literature on image super-resolution (SR) assumes the...

11 Manuel Fritsche, et al. ∙

research

∙ 11/04/2019

AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

This paper reviews the AIM 2019 challenge on constrained example-based s...

12 Kai Zhang, et al. ∙

research

∙ 08/23/2019

Learning Filter Basis for Convolutional Neural Network Compression

Convolutional neural networks (CNNs) based solutions have achieved state...

12 Yawei Li, et al. ∙

research

∙ 06/17/2019

Exemplar Guided Face Image Super-Resolution without Facial Landmarks

Nowadays, due to the ubiquitous visual media there are vast amounts of a...

5 Berk Dogan, et al. ∙

research

∙ 04/01/2019

Learning Content-Weighted Deep Image Compression

Learning-based lossy image compression usually involves the joint optimi...

10 Mu Li, et al. ∙

research

∙ 10/03/2018

PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report

This paper reviews the first challenge on efficient perceptual image enh...

2 Andrey Ignatov, et al. ∙

research

∙ 07/30/2018

Multi-bin Trainable Linear Unit for Fast Image Restoration Networks

Tremendous advances in image restoration tasks such as denoising and sup...

0 Shuhang Gu, et al. ∙

research

∙ 01/15/2018

Efficient Trimmed Convolutional Arithmetic Encoding for Lossless Image Compression

Arithmetic encoding is an essential class of coding techniques which hav...

0 Mu Li, et al. ∙

research

∙ 04/11/2017

Learning Deep CNN Denoiser Prior for Image Restoration

Model-based optimization methods and discriminative learning methods hav...

0 Kai Zhang, et al. ∙

research

∙ 03/30/2017

Learning Convolutional Networks for Content-weighted Image Compression

Lossy image compression is generally formulated as a joint rate-distorti...

0 Mu Li, et al. ∙

research

∙ 12/03/2015

Weighted Schatten p-Norm Minimization for Image Denoising and Background Subtraction

Low rank matrix approximation (LRMA), which aims to recover the underlyi...

0 Yuan Xie, et al. ∙

research

∙ 05/23/2014

On the Optimal Solution of Weighted Nuclear Norm Minimization

In recent years, the nuclear norm minimization (NNM) problem has been at...

0 Qi Xie, et al. ∙

Shuhang Gu

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