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024 7 _a10.1007/978-3-030-69532-3
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245 1 0 _aComputer Vision – ACCV 2020
_h[electronic resource] :
_b15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part II /
_cedited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXVIII, 718 p. 260 illus.
_bonline resource.
336 _atext
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337 _acomputer
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_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v12623
505 0 _aLow-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.
520 _aThe 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.
650 0 _aComputer vision.
650 0 _aArtificial intelligence.
650 0 _aPattern recognition systems.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 1 4 _aComputer Vision.
650 2 4 _aArtificial Intelligence.
650 2 4 _aAutomated Pattern Recognition.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Engineering and Networks.
700 1 _aIshikawa, Hiroshi.
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700 1 _aLiu, Cheng-Lin.
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700 1 _aPajdla, Tomas.
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700 1 _aShi, Jianbo.
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710 2 _aSpringerLink (Online service)
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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