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Lieferstatus:	i.d.R. innert 5-10 Tagen versandfertig
Veröffentlichung:	November 2022
Genre:	EDV / Informatik
	Applications / computerscience / ConferenceProceedings / Informatics / Research
ISBN:	9783031200854
EAN-Code:	9783031200854
Verlag:	Springer
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D 44 mm
Gewicht:	1200 gr
Seiten:	808
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

MHR-Net: Multiple-Hypothesis Reconstruction of Non-rigid Shapes from 2D Views.- Depth Map Decomposition for Monocular Depth Estimation.- Monitored Distillation for Positive Congruent Depth Completion.- Resolution-Free Point Cloud Sampling Network with Data Distillation.- Organic Priors in Non-rigid Structure from Motion.- Perspective Flow Aggregation for Data-Limited 6D Object Pose Estimation.- DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks.- CHORE: Contact, Human and Object REconstruction from a Single RGB Image.- Learned Vertex Descent: A New Direction for 3D Human Model Fitting.- Self-Calibrating Photometric Stereo by Neural Inverse Rendering.- 3D Clothed Human Reconstruction in the Wild.- Directed Ray Distance Functions for 3D Scene Reconstruction.- Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation from Monocular RGB Image.- Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression.- CostDCNet: Cost Volume Based Depth Completion for a Single RGB-D Image.- ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization.- 3D Siamese Transformer Network for Single Object Tracking on Point Clouds.- Object Wake-Up: 3D Object Rigging from a Single Image.- IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-View Human Reconstruction.- Realistic One-Shot Mesh-Based Head Avatars.- A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks.- Neural Light Field Estimation for Street Scenes with Differentiable Virtual Object Insertion.- Perspective Phase Angle Model for Polarimetric 3D Reconstruction.- DeepShadow: Neural Shape from Shadow.- Camera Auto-Calibration from the Steiner Conic of the Fundamental Matrix.- Super-Resolution 3D Human Shape from a Single Low-Resolution Image.- Minimal Neural Atlas: Parameterizing Complex Surfaces with Minimal Charts and Distortion.- ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing.- CATRE: Iterative Point Clouds Alignment for Category-Level Object Pose Refinement.- Optimization over Disentangled Encoding: Unsupervised Cross-Domain Point Cloud Completion via Occlusion Factor Manipulation.- Unsupervised Learning of 3D Semantic Keypoints with Mutual Reconstruction.- MvDeCor: Multi-View Dense Correspondence Learning for Fine-Grained 3D Segmentation.- SUPR: A Sparse Unified Part-Based Human Representation.- Revisiting Point Cloud Simplification: A Learnable Feature Preserving Approach.- Masked Autoencoders for Point Cloud Self-Supervised Learning.- Intrinsic Neural Fields: Learning Functions on Manifolds.- Skeleton-Free Pose Transfer for Stylized 3D Characters.- Masked Discrimination for Self-Supervised Learning on Point Clouds.- FBNet: Feedback Network for Point Cloud Completion.- Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds.-A Level Set Theory for Neural Implicit Evolution under Explicit Flows.- Efficient Point Cloud Analysis Using Hilbert Curve.