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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:	9783031198236
EAN-Code:	9783031198236
Verlag:	Springer
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D 43 mm
Gewicht:	1188 gr
Seiten:	800
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

ARAH: Animatable Volume Rendering of Articulated Human SDFs.- ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer.- NDF: Neural Deformable Fields for Dynamic Human Modelling.- Neural Density-Distance Fields.- NeXT: Towards High Quality Neural Radiance Fields via Multi-Skip Transformer.- Learning Online Multi-sensor Depth Fusion.- BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-Scale Scene Rendering.- Decomposing the Tangent of Occluding Boundaries according to Curvatures and Torsions.- NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors.- Generalizable Patch-Based Neural Rendering.- Improving RGB-D Point Cloud Registration by Learning Multi-Scale Local Linear Transformation.- Real-Time Neural Character Rendering with Pose-Guided Multiplane Images.- SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views.- Disentangling Object Motion and Occlusion for Unsupervised Multi-Frame Monocular Depth.- Depth Field Networks for Generalizable Multi-View Scene Representation.- Context-Enhanced Stereo Transformer.- PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo Matching.- Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images.- Latency-Aware Collaborative Perception.- TensoRF: Tensorial Radiance Fields.- NeFSAC: Neurally Filtered Minimal Samples.- SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data.- HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields.- NeuMan: Neural Human Radiance Field from a Single Video.- TAVA: Template-Free Animatable Volumetric Actors.- EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching.- Relative Pose from SIFT Features.- Selection and Cross Similarity for Event-Image Deep Stereo.- D3Net: A Unified Speaker-Listener Architecture for 3D Dense Captioning and Visual Grounding.- CIRCLE: Convolutional Implicit Reconstruction and Completion for Large-Scale Indoor Scene.- ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild.- 4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding.- Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space.- Solution Space Analysis of Essential Matrix Based on Algebraic Error Minimization.- Approximate Differentiable Rendering with Algebraic Surfaces.- CoVisPose: Co-Visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360° Indoor Panoramas.- Affine Correspondences between Multi-Camera Systems for 6DOF Relative Pose Estimation.- GraphFit: Learning Multi-Scale Graph-Convolutional Representation for Point Cloud Normal Estimation.- IS-MVSNet: Importance Sampling-Based MVSNet.- Point Scene Understanding via Disentangled Instance Mesh Reconstruction.- DiffuStereo: High Quality Human Reconstruction via Diffusion-Based Stereo Using Sparse Cameras.- Space-Partitioning RANSAC.