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  • Produktbild: Computer Vision – ECCV 2022
  • Produktbild: Computer Vision – ECCV 2022
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Computer Vision – ECCV 2022 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXIII

Aus der Reihe Lecture Notes in Computer Science
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104,99 € UVP 120,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

02.11.2022

Herausgeber

Shai Avidan + weitere

Verlag

Springer

Seitenzahl

749

Maße (L/B/H)

23,5/15,5/4,4 cm

Gewicht

1200 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-19826-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

02.11.2022

Herausgeber

Verlag

Springer

Seitenzahl

749

Maße (L/B/H)

23,5/15,5/4,4 cm

Gewicht

1200 g

Auflage

1st edition 2022

Sprache

Englisch

ISBN

978-3-031-19826-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Computer Vision – ECCV 2022
  • Produktbild: Computer Vision – ECCV 2022
  • 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 Pairsfor 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.