06808nam 22006615 450 991048479100332120251113182757.03-030-69535-210.1007/978-3-030-69535-4(CKB)4100000011781456(MiAaPQ)EBC6501091(DE-He213)978-3-030-69535-4(PPN)253858836(EXLCZ)99410000001178145620210224d2021 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierComputer Vision – ACCV 2020 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part III /edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi1st ed. 2021.Cham :Springer International Publishing :Imprint: Springer,2021.1 online resource (XVIII, 757 p. 245 illus., 229 illus. in color.) Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;126243-030-69534-4 Recognition and Detection -- End-to-end Model-based Gait Recognition -- Horizontal Flipping Assisted Disentangled Feature Learning for Semi-Supervised Person Re-Identification -- MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings -- Backbone Based Feature Enhancement for Object Detection -- Long-Term Cloth-Changing Person Re-identification -- Any-Shot Object Detection -- Background Learnable Cascade for Zero-Shot Object Detection -- Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation -- COG: COnsistent data auGmentation for object perception -- Synthesizing the Unseen for Zero-shot Object Detection -- Fully Supervised and Guided Distillation for One-Stage Detectors -- Visualizing Color-wise Saliency of Black-Box Image Classification Models -- ERIC: Extracting Relations Inferred from Convolutions -- D2D: Keypoint Extraction with Describe to Detect Approach -- Accurate Arbitrary-Shaped Scene Text Detection via Iterative Polynomial ParameterRegression -- Adaptive Spotting: Deep Reinforcement Object Search in 3D Point Clouds -- Efficient Large-Scale Semantic Visual Localization in 2D Maps -- Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild -- Scale-Aware Polar Representation for Arbitrarily-Shaped Text Detection -- Branch Interaction Network for Person Re-identification -- BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images -- Jointly Discriminating and Frequent Visual Representation Mining -- Discrete Spatial Importance-Based Deep Weighted Hashing -- Low-level Sensor Fusion Network for 3D Vehicle Detection using Radar Range-Azimuth Heatmap and Monocular Image -- MLIFeat: Multi-level information fusion based deep local features -- CLASS: Cross-Level Attention and Supervision for Salient Objects Detection -- Cascaded Transposed Long-range Convolutions for Monocular Depth Estimation -- Optimization, Statistical Methods, and Learning -- Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks -- Large-Scale Cross-Domain Few-Shot Learning -- Channel Pruning for Accelerating Convolutional Neural Networks via Wasserstein Metric -- Progressive Batching for Efficient Non-linear Least Squares -- Fast and Differentiable Message Passing on Pairwise Markov Random Fields -- A Calibration Method for the Generalized Imaging Model with Uncertain Calibration Target Coordinates -- Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network -- Towards Fast and Robust Adversarial Training for Image Classification -- Few-Shot Zero-Shot Learning: Knowledge Transfer with Less Supervision -- Lossless Image Compression Using a Multi-Scale Progressive Statistical Model -- Spatial Class Distribution Shift in Unsupervised Domain Adaptation: Local Alignment Comes to Rescue -- Robot Vision -- Point Proposal based Instance Segmentation with Rectangular Masks for Robot Picking Task -- Multi-task Learning with Future States for Vision-based Autonomous Driving -- MTNAS: Search Multi-Task Networks for Autonomous Driving -- Compact and Fast Underwater Segmentation Network for Autonomous Underwater Vehicles -- L2R GAN: LiDAR-to-Radar Translation -- V2A - Vision to Action: Learning robotic arm actions based on vision and language -- To Filter Prune, or to Layer Prune, That Is The Question.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 ;12624Computer visionArtificial intelligenceComputer engineeringComputer networksPattern recognition systemsComputer VisionArtificial IntelligenceComputer Engineering and NetworksAutomated Pattern RecognitionComputer Engineering and NetworksComputer vision.Artificial intelligence.Computer engineering.Computer networks.Pattern recognition systems.Computer Vision.Artificial Intelligence.Computer Engineering and Networks.Automated Pattern Recognition.Computer Engineering and Networks.006.37Ishikawa Hiroshiedthttp://id.loc.gov/vocabulary/relators/edtLiu Cheng-Linedthttp://id.loc.gov/vocabulary/relators/edtPajdla Tomášedthttp://id.loc.gov/vocabulary/relators/edtShi Jianboedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910484791003321Computer vision-ACCV 20201890247UNINA