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_aComputer Vision - ACCV 2020 _h[electronic resource] : _b15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part I / _cedited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
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300 |
_aXVIII, 740 p. 10 illus. _bonline resource. |
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_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12622 |
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505 | 0 | _a3D Computer Vision -- Weakly-supervised Reconstruction of 3D Objects with Large Shape Variation from Single In-the-Wild Images -- HPGCNN: Hierarchical Parallel Group Convolutional Neural Networks for Point Clouds Processing -- 3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings -- Reconstructing Creative Lego Models, George Tattersall -- Multi-View Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People -- Learning Global Pose Features in Graph Convolutional Networks for 3D Human Pose Estimation -- SGNet: Semantics Guided Deep Stereo Matching -- Reconstructing Human Body Mesh from Point Clouds by Adversarial GP Network -- SDP-Net: Scene Flow Based Real-time Object Detection and Prediction from Sequential 3D Point Clouds -- SAUM: Symmetry-Aware Upsampling Module for Consistent Point Cloud Completion -- Faster Self-adaptive Deep Stereo -- AFN: Attentional Feedback Network based 3D Terrain Super-Resolution -- Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds -- Anatomy and Geometry Constrained One-Stage Framework for 3D Human Pose Estimation -- DeepVoxels++: Enhancing the Fidelity of Novel View Synthesis from 3D Voxel Embeddings -- Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media -- Homography-based Egomotion Estimation Using Gravity and SIFT Features -- Mapping of Sparse 3D Data using Alternating Projection -- Best Buddies Registration for Point Clouds -- Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data -- Dynamic Depth Fusion and Transformation for Monocular 3D Object Detection -- Attention-Aware Feature Aggregation for Real-time Stereo Matching on Edge Devices -- FKAConv: Feature-Kernel Alignment for Point Cloud Convolution -- Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks -- IAFA: Instance-Aware Feature Aggregation for 3D Object Detection from a Single Image -- Attended-Auxiliary Supervision Representation for Face Anti-spoofing -- 3D Object Detection from Consecutive Monocular Images -- Data-Efficient Ranking Distillation for Image Retrieval -- Quantum Robust Fitting -- HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning -- Segmentation and Grouping -- RGB-D Co-attention Network for Semantic Segmentation -- Semantics through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation -- Dense Dual-Path Network for Real-time Semantic Segmentation -- Learning More Accurate Features for Semantic Segmentation in CycleNet -- 3D Guided Weakly Supervised Semantic Segmentation -- Real-Time Segmentation Networks should be Latency Aware -- Mask-Ranking Network for Semi-Supervised Video Object Segmentation -- SDCNet: Size Divide and Conquer Network for Salient Object Detection -- Bidirectional Pyramid Networks for Semantic Segmentation -- DEAL: Difficulty-aware Active Learning for Semantic Segmentation -- EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention Fusion -- Local Context Attention for Salient Object Segmentation -- Generic Image Segmentation in Fully Convolutional Networks by Superpixel Merging Map. | |
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. _991358 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aComputer engineering. _910164 |
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650 | 0 |
_aComputer networks . _931572 |
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650 | 0 |
_aPattern recognition systems. _93953 |
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650 | 1 | 4 |
_aComputer Vision. _991359 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aComputer Engineering and Networks. _991360 |
650 | 2 | 4 |
_aComputer Communication Networks. _991361 |
650 | 2 | 4 |
_aAutomated Pattern Recognition. _931568 |
700 | 1 |
_aIshikawa, Hiroshi. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _929891 |
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700 | 1 |
_aLiu, Cheng-Lin. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _991362 |
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700 | 1 |
_aPajdla, Tomas. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _991363 |
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700 | 1 |
_aShi, Jianbo. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _991364 |
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710 | 2 |
_aSpringerLink (Online service) _991365 |
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773 | 0 | _tSpringer Nature eBook | |
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_iPrinted edition: _z9783030695248 |
776 | 0 | 8 |
_iPrinted edition: _z9783030695262 |
830 | 0 |
_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12622 _991366 |
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