Computer vision -- ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, revised selected papers
著者
書誌事項
Computer vision -- ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, revised selected papers
(Lecture notes in computer science, 12623 . LNCS sublibrary ; SL 6 . Image processing,
Springer, c2021
- pt. 2
- タイトル別名
-
ACCV 2020
大学図書館所蔵 全1件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
"The Asian Conference on Computer Vision (ACCV) 2020, originally planned to take place in Kyoto, Japan, was held online during November 30 - December 4, 2020."--Preface
Other editors: Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Includes bibliographical references and author index
内容説明・目次
内容説明
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.
目次
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 usingGlobal 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 toDense 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.
「Nielsen BookData」 より