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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:	9783031198267
EAN-Code:	9783031198267
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:

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.