Computer vision - ECCV 2022 = 17th E...
European Conference on Computer Vision (2022 :)

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  • Computer vision - ECCV 2022 = 17th European Conference, Tel Aviv, Israel, October 23-27, 2022 : proceedings.. Part XXXIII /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Computer vision - ECCV 2022/ edited by Shai Avidan ... [et al.].
    其他題名: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022 : proceedings.
    其他題名: ECCV 2022
    其他作者: Avidan, Shai.
    團體作者: European Conference on Computer Vision
    出版者: Cham :Springer Nature Switzerland : : 2022.,
    面頁冊數: lvi, 749 p. :ill., digital ;24 cm.
    內容註: SimpleRecon: 3D Reconstruction without 3D Convolutions -- Structure and Motion from Casual Videos -- What Matters for 3D Scene Flow Network -- Correspondence Reweighted Translation Averaging -- Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images -- GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs -- Objects Can Move: 3D Change Detection by Geometric Transformation Consistency -- Language-Grounded Indoor 3D Semantic Segmentation in the Wild -- Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs -- Deforming Radiance Fields with Cages -- FLEX: Extrinsic Parameters-Free Multi-View 3D Human Motion Reconstruction -- MODE: Multi-View Omnidirectional Depth Estimation with 360° Cameras -- GigaDepth: Learning Depth from Structured Light with Branching Neural Networks -- ActiveNeRF: Learning Where to See with Uncertainty Estimation -- PoserNet: Refining Relative Camera Poses Exploiting Object Detections -- Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction & Pose Estimation -- Unbiased Gradient Estimation for Differentiable Surface Splatting via Poisson Sampling -- Towards Learning Neural Representations from Shadows -- Class-Incremental Novel Class Discovery -- Unknown-Oriented Learning for Open Set Domain Adaptation -- Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation -- DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation -- Class-Agnostic Object Counting Robust to Intraclass Diversity -- Burn after Reading: Online Adaptation for Cross-Domain Streaming Data -- Mind the Gap in Distilling StyleGANs -- Improving Test-Time Adaptation via Shift-Agnostic Weight Regularization and Nearest Source Prototypes -- Learning Instance-Specific Adaptation for Cross-Domain Segmentation -- RegionCL: Exploring Contrastive Region Pairs for Self-Supervised Representation Learning -- Long-Tailed Class Incremental Learning -- DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning -- Adversarial Partial Domain Adaptation by Cycle Inconsistency -- Combating Label Distribution Shift for Active Domain Adaptation -- GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation -- CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation -- A Unified Framework for Domain Adaptive Pose Estimation -- A Broad Study of Pre-training for Domain Generalization and Adaptation -- Prior Knowledge Guided Unsupervised Domain Adaptation -- GCISG: Guided Causal Invariant Learning for Improved Syn-to-Real Generalization -- AcroFOD: An Adaptive Method for Cross-Domain Few-Shot Object Detection -- Unsupervised Domain Adaptation for One-Stage Object Detector Using Offsets to Bounding Box -- Visual Prompt Tuning -- Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gap.
    Contained By: Springer Nature eBook
    標題: Computer vision - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-19827-4
    ISBN: 9783031198274
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