06438nam 22006855 450 991048468790332120251113191146.03-030-69532-810.1007/978-3-030-69532-3(CKB)4100000011781455(MiAaPQ)EBC6506902(Au-PeEL)EBL6506902(OCoLC)1241066422(PPN)253858798(DE-He213)978-3-030-69532-3(EXLCZ)99410000001178145520210226d2021 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierComputer 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 Shi1st ed. 2021.Cham :Springer International Publishing :Imprint: Springer,2021.1 online resource (733 pages)Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;126233-030-69531-X 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.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.Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;12623Computer visionArtificial intelligencePattern recognition systemsComputer engineeringComputer networksComputer VisionArtificial IntelligenceAutomated Pattern RecognitionComputer Engineering and NetworksComputer Engineering and NetworksComputer vision.Artificial intelligence.Pattern recognition systems.Computer engineering.Computer networks.Computer Vision.Artificial Intelligence.Automated Pattern Recognition.Computer Engineering and Networks.Computer Engineering and Networks.006.3Ishikawa HiroshiMiAaPQMiAaPQMiAaPQBOOK9910484687903321Computer vision-ACCV 20201890247UNINA