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Computer Vision – ACCV 2020: 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part VI de Hiroshi Ishikawa

Computer Vision – ACCV 2020: 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part VI: Lecture Notes in Computer Science, cartea 12627

Editat de Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
en Limba Engleză Paperback – 26 feb 2021
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.
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Specificații

ISBN-13: 9783030695439
ISBN-10: 3030695433
Pagini: 705
Ilustrații: XVIII, 705 p. 262 illus., 252 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics

Locul publicării:Cham, Switzerland

Cuprins

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.