Description

Book Synopsis
This book constitutes the refereed post-conference proceedings of the workshops held at the 16th Asian Conference on Computer Vision, ACCV 2022, which took place in Macao, China, in December 2022.
The 25 papers included in this book were carefully reviewed and selected from 40 submissions. They have been organized in topical sections as follows: Learning with limited data for face analysis; adversarial machine learning towards advanced vision systems; computer vision for medical computing; machine learning and computing for visual semantic analysis; vision transformers theory and applications; and deep learning-based small object detection from images and videos.



Table of Contents
Learning with Limited Data for Face Analysis.- FAPN: Face Alignment Propagation Network for Face Video Super-Resolution.- Micro-expression recognition using a shallow ConvLSTM-based network.- Adversarial Machine Learning towards Advanced Vision Systems.- ADVFilter: Adversarial Example Generated by Perturbing Optical Path.- Enhancing Federated Learning Robustness Through clustering Non-IID Features.- Towards Improving the Anti-attack Capability of the RangeNet++.- Computer Vision for Medical Computing.- Ensemble Model of Visual Transformer and CNN Helps BA Diagnosis for Doctors in Underdeveloped Areas.- Understanding Tumor Micro Environment using Graph theory.- Handling Domain Shift for Lesion Detection via Semi-Supervised Domain Adaptation.- Photorealistic Facial Wrinkles Removal.- Improving Segmentation of Breast Arterial Calcifications from Digital Mammography: Good Annotation Is All You Need.- Machine Learning and Computing for Visual Semantic Analysis.- Towards Scene Understanding for Autonomous Operations on Airport Aprons.- Lightweight Hyperspectral Image Reconstruction Network with Deep Feature Hallucination.- A Transformer-based Model for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Muti-p.- CaltechFN: Distorted and Partially Occluded Digits.- Temporal Extension Topology Learning for Video-based Person Re-Identification.- Deep RGB-driven Learning Network for Unsupervised Hyperspectral Image Super-resolution.- Gift from nature: Potential Energy Minimization for explainable dataset distillation.- Object Centric Point Sets Feature Learning with Matrix Decomposition.- Aerial Image Segmentation via Noise Dispelling and Content Distilling.- Vision Transformers Theory and Applications.- Temporal Cross-attention for Action Recognition.- Transformer Based Motion In-Betweening.- Convolutional point Transformer.- Cross-Attention Transformer for Video Interpolation.- Deep Learning-Based Small Object Detection from Images and Videos.- Evaluating and Bench-marking Object Detection Models for Traffic Sign and Traffic Light Datasets.- Exploring Spatial-temporal Instance Relationships In an Intermediate Domain For Image-to-video Object Detection.

Computer Vision – ACCV 2022 Workshops: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Revised Selected Papers

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A Paperback by Yinqiang Zheng, Hacer Yalim Keleş, Piotr Koniusz

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    View other formats and editions of Computer Vision – ACCV 2022 Workshops: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Revised Selected Papers by Yinqiang Zheng

    Publisher: Springer International Publishing AG
    Publication Date: 09/03/2023
    ISBN13: 9783031270659, 978-3031270659
    ISBN10: 3031270657

    Description

    Book Synopsis
    This book constitutes the refereed post-conference proceedings of the workshops held at the 16th Asian Conference on Computer Vision, ACCV 2022, which took place in Macao, China, in December 2022.
    The 25 papers included in this book were carefully reviewed and selected from 40 submissions. They have been organized in topical sections as follows: Learning with limited data for face analysis; adversarial machine learning towards advanced vision systems; computer vision for medical computing; machine learning and computing for visual semantic analysis; vision transformers theory and applications; and deep learning-based small object detection from images and videos.



    Table of Contents
    Learning with Limited Data for Face Analysis.- FAPN: Face Alignment Propagation Network for Face Video Super-Resolution.- Micro-expression recognition using a shallow ConvLSTM-based network.- Adversarial Machine Learning towards Advanced Vision Systems.- ADVFilter: Adversarial Example Generated by Perturbing Optical Path.- Enhancing Federated Learning Robustness Through clustering Non-IID Features.- Towards Improving the Anti-attack Capability of the RangeNet++.- Computer Vision for Medical Computing.- Ensemble Model of Visual Transformer and CNN Helps BA Diagnosis for Doctors in Underdeveloped Areas.- Understanding Tumor Micro Environment using Graph theory.- Handling Domain Shift for Lesion Detection via Semi-Supervised Domain Adaptation.- Photorealistic Facial Wrinkles Removal.- Improving Segmentation of Breast Arterial Calcifications from Digital Mammography: Good Annotation Is All You Need.- Machine Learning and Computing for Visual Semantic Analysis.- Towards Scene Understanding for Autonomous Operations on Airport Aprons.- Lightweight Hyperspectral Image Reconstruction Network with Deep Feature Hallucination.- A Transformer-based Model for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Muti-p.- CaltechFN: Distorted and Partially Occluded Digits.- Temporal Extension Topology Learning for Video-based Person Re-Identification.- Deep RGB-driven Learning Network for Unsupervised Hyperspectral Image Super-resolution.- Gift from nature: Potential Energy Minimization for explainable dataset distillation.- Object Centric Point Sets Feature Learning with Matrix Decomposition.- Aerial Image Segmentation via Noise Dispelling and Content Distilling.- Vision Transformers Theory and Applications.- Temporal Cross-attention for Action Recognition.- Transformer Based Motion In-Betweening.- Convolutional point Transformer.- Cross-Attention Transformer for Video Interpolation.- Deep Learning-Based Small Object Detection from Images and Videos.- Evaluating and Bench-marking Object Detection Models for Traffic Sign and Traffic Light Datasets.- Exploring Spatial-temporal Instance Relationships In an Intermediate Domain For Image-to-video Object Detection.

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