Computer Vision - ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part II / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi.

Format:

Book

Contributor:

Ishikawa, Hiroshi, Editor.

Liu, Cheng-Lin, Editor.

Pajdla, Tomáš, Editor.

Shi, Jianbo, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12623

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12623

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Pattern recognition systems.

Computer engineering.

Computer networks.

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Computer Engineering and Networks.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Computer Engineering and Networks.

Physical Description:

1 online resource (XVIII, 718 pages) : 260 illustrations

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.

Contents:

Low-Level Vision, Image Processing

Image Inpainting with Onion Convolutions

Accurate and Efficient Single Image Super-Resolution with Matrix Channel Attention Network

Second-order Camera-aware Color Transformation for Cross-domain Person Re-identification

CS-MCNet:A Video Compressive Sensing Reconstruction Network with Interpretable Motion Compensation

MCGKT-Net: Multi-level Context Gating Knowledge Transfer Network for Single Image Deraining

Degradation Model Learning for Real-World Single Image Super-resolution

Chromatic Aberration Correction Using Cross-Channel Prior in Shearlet Domain

Raw-Guided Enhancing Reprocess of Low-Light Image via Deep Exposure Adjustment

Robust High Dynamic Range (HDR) Imaging with Complex Motion and Parallax

Low-light Color Imaging via Dual Camera Acquisition

Frequency Attention Network: Blind Noise Removal for Real Images

Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network

Color Enhancement using Global Parameters and Local Features Learning

An Efficient Group Feature Fusion Residual Network for Image Super-Resolution

Adversarial Image Composition with Auxiliary Illumination

Overwater Image Dehazing via Cycle-Consistent Generative Adversarial Network

Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning

Multi-scale Attentive Residual Dense Network for Single Image Rain Removal

FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization

Human Motion Deblurring using Localized Body Prior

Synergistic Saliency and Depth Prediction for RGB-D Saliency Detection

Deep Snapshot HDR Imaging Using Multi-Exposure Color Filter Array

Deep Priors inside an Unrolled and Adaptive Deconvolution Model

Motion and Tracking

Adaptive Spatio-Temporal Regularized Correlation Filters for UAV-based Tracking

Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation

Self-supervised Sparse to Dense Motion Segmentation

Recursive Bayesian Filtering for Multiple Human Pose Tracking from Multiple Cameras

Adversarial Refinement Network for Human Motion Prediction

Semantic Synthesis of Pedestrian Locomotion

Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation

Visual Tracking by TridentAlign and Context Embedding

Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking

A Two-Stage Minimum Cost Multicut Approach to Self-Supervised Multiple Person Tracking

Learning Local Feature Descriptors for Multiple Object Tracking

VAN: Versatile Affinity Network for End-to-end Online Multi-Object Tracking

COMET: Context-Aware IoU-Guided Network for Small Object Tracking

Adversarial Semi-Supervised Multi-Domain Tracking

Tracking-by-Trackers with a Distilled and Reinforced Model

Motion Prediction Using Temporal Inception Module

A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking

Modeling Cross-Modal interaction in a Multi-detector, Multi-modal Tracking Framework

Dense Pixel-wise Micro-motion Estimation of Object Surface by using Low Dimensional Embedding of Laser Speckle Pattern.

Other Format:

Printed edition:

ISBN:

978-3-030-69532-3

9783030695323

Access Restriction:

Restricted for use by site license.