Computer Vision - ECCV 2020 Workshops : Glasgow, UK, August 23-28, 2020, Proceedings, Part III / edited by Adrien Bartoli, Andrea Fusiello.

Format:

Book

Contributor:

Bartoli, Adrien, Editor.

Fusiello, Andrea, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12537

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12537

Language:

English

Subjects (All):

Computer vision.

Computer Vision.

Local Subjects:

Computer Vision.

Physical Description:

1 online resource (XXVIII, 762 pages) : 356 illustrations, 338 illustrations in color.

Edition:

1st ed. 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part III includes the Advances in Image Manipulation Workshop and Challenges. .

Contents:

W24 - Advances in Image Manipulation Workshop and Challenges

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Residual Feature Distillation Network for Lightweight Image Super-Resolution. -Efficient Image Super-Resolution using Pixel Attention

LarvaNet: Hierarchical Super-Resolution via Multi-exit Architecture

Efficient Super-Resolution using MobileNetV3

Multi-Attention Based Ultra Lightweight Image Super-Resolution

Adaptive Hybrid Composition based Super-Resolution Network via Fine-grained Channel Pruning

IdleSR: E cient Super-Resolution Network with Multi-Scale IdleBlocks

IM 2020 Challenge on Learned Image Signal Processing Pipeline

EEDNet: Enhanced Encoder Decoder Network for AutoISP

AWNet: Attentive Wavelet Network for ImageISP

PyNET-CA: Enhanced PyNET with Channel Attention for End-to-end Mobile Image Signal Processing

AIM 2020 Challenge on Rendering Realistic Bokeh

BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh

Bokeh Rendering from Defocus Estimation

Human Motion Transfer from Poses in the Wild

FamilyGAN: Generating Kin Face Images using Generative Adversarial Networks

Genetic-GAN: Synthesizing images between two domains by genetic crossover

GIA-Net: Global Information Aware Network for Low-light Imaging

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

A Benchmark for Burst Color Constancy

Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Real Image Super Resolution via Heterogeneous Model Ensemble using GP-NAS

Enhanced Adaptive Dense Connection Single Image Super-Resolution

Self-Calibrated Attention Neural Network for Real-World Super Resolution

FAN: Frequency Aggregation Network for Real Image Super-resolution

Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution

AIM 2020: Scene Relighting and Illumination Estimation Challenge

WDRN : A Wavelet Decomposed RelightNet for Image Relighting

SA-AE for Any-to-any Relighting

Deep Relighting Networks for Image Light Source Manipulation

LightNet: Deep Learning based Illumination Estimation from Virtual Images

An Ensemble Neural Network for Scene Relighting with Light Classification

Long-Term Human Video Generation of Multiple Futures Using Poses

AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs

Unconstrained Text Detection in Manga: a New Dataset and Baseline

Joint Demosaicking and Denoising for CFA and MSFA Images using a Mosaic-Adaptive Dense Residual Network

Gated Texture CNN for Efficient and Configurable Image Denoising

Quantized Warping and Residual Temporal Integration for Video Super-Resolution on Fast Motions

Pyramidal Edge-maps and Attention based Guided Thermal Super-resolution

AIM 2020 Challenge on Image Extreme Inpainting

Fast Light-Weight Network for Extreme Image Inpainting Challenge.

Other Format:

Printed edition:

ISBN:

978-3-030-67070-2

9783030670702

Access Restriction:

Restricted for use by site license.