Computer Vision - ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part VI / 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, 12627

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12627

Language:

English

Subjects (All):

Computer vision.

Computer engineering.

Computer networks.

Artificial intelligence.

Pattern recognition systems.

Application software.

Computer Vision.

Computer Engineering and Networks.

Artificial Intelligence.

Automated Pattern Recognition.

Computer and Information Systems Applications.

Local Subjects:

Computer Vision.

Computer Engineering and Networks.

Artificial Intelligence.

Automated Pattern Recognition.

Computer and Information Systems Applications.

Physical Description:

1 online resource (XVIII, 705 pages) : 262 illustrations, 252 illustrations in color.

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:

Applications of Computer Vision, Vision for X

Query by Strings and Return Ranking Word Regions with Only One Look

Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement

FootNet: An efficient convolutional network for multiview 3D foot reconstruction

Synthetic-to-real domain adaptation for lane detection

RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations

DoFNet: Depth of Field Difference Learning for Detecting Image Forgery

Explaining image classifiers by removing input features using generative models

Do We Need Sound for Sound Source Localization?

Modular Graph Attention Network for Complex Visual Relational Reasoning

CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON

Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion

Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation

Sketch-to-Art: Synthesizing Stylized Art Images From Sketches

Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation

SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection

Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion

Audiovisual Transformer with Instance Attention for Audio-Visual Event Localization

Watch, read and lookup: learning to spot signs from multiple supervisors

Domain-transferred Face Augmentation Network

Pose Correction Algorithm for Relative Frames between Keyframes in SLAM

Dense-Scale Feature Learning in Person Re-Identification

Class-incremental Learning with Rectified Feature-Graph Preservation

Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation

Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features

Visually Guided Sound Source Separation using Cascaded Opponent Filter Network

Channel Recurrent Attention Networks for Video Pedestrian Retrieval

In Defense of LSTMs for Addressing Multiple Instance Learning Problems

Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score

Show, Conceive and Tell: Image Captioning with Prospective Linguistic Information

Datasets and Performance Analysis

RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network

Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning

Compensating for the Lack of Extra Training Data by Learning Extra Representation

Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance

OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets

Pre-training without Natural Images

TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines

A Day on Campus - An Anomaly Detection Dataset for Events in a Single Camera

A Benchmark and Baseline for Language-Driven Image Editing

Self-supervised Learning of Orc-Bert Augmentator for Recognizing Few-Shot Oracle Characters

Understanding Motion in Sign Language: A New Structured Translation Dataset

FreezeNet: Full Performance by Reduced Storage Costs.

Other Format:

Printed edition:

ISBN:

978-3-030-69544-6

9783030695446

Access Restriction:

Restricted for use by site license.