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Computer Vision – ECCV 2024 Workshops -

Computer Vision – ECCV 2024 Workshops

Milan, Italy, September 29–October 4, 2024, Proceedings, Part XVIII
Buch | Softcover
LV, 382 Seiten
2025
Springer International Publishing (Verlag)
978-3-031-91671-7 (ISBN)
CHF 122,80 inkl. MwSt
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The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29 October 4, 2024. 

These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of workshops and distribution of the workshop papers in the LNCS volumes can be found in the preface that is freely accessible online.

.- DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights using the Fisher Diagonal.
.- Prompt Sliders for Fine-Grained Control, Editing and Erasing of Concepts in Diffusion Models.
.- Aligning Vision Language Models with Contrastive Learning.
.- Open-set object detection: towards unified problem formulation and benchmarking.
.- Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts.
.- SOOD-ImageNet: a Large-Scale Dataset for Semantic Out-Of-Distribution Image Classification and Semantic Segmentation.
.- Online Stochastic Optimization for Data with Temporal Dependencies.
.- A Lost Opportunity for Vision-Language Models: A Comparative Study of Online Test-Time Adaptation for Vision-Language Models.
.- OSSA: Unsupervised One-Shot Style Adaptation.
.- ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer.
.- Open-set Plankton Recognition.
.- Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?.
.- On the Potential of Open-Vocabulary Models for Object Detection in Unusual Street Scenes.
.- Source-Free Domain Adaptation for YOLO Object Detection.
.- Task-Specific Adaptation of Segmentation Foundation Model via Prompt Learning.
.- Utilizing Class-Agnostic Point-to-Box Regressors as Object Proposal Generators.
.- Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive Perspective.
.- Improving Generalization in Visual Reasoning via Self-Ensemble.
.- BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation.
.- Image Translation with Kernel Prediction Networks for Semantic Segmentation.
.- Robust fine-tuning and adaptation of zero-shot models via adaptive weightspace ensembling.
.- Robustness to Spurious Correlation: A Comprehensive Review.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Zusatzinfo LV, 382 p. 116 illus., 114 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Schlagworte Artificial Intelligence • computer vision • Human-Computer Interaction (HCI) • Image Analysis • image coding • Image Processing • image reconstruction • Image Segmentation • learning • machine learning • Object recognition • pattern recognition • reconstruction • Signal Processing
ISBN-10 3-031-91671-9 / 3031916719
ISBN-13 978-3-031-91671-7 / 9783031916717
Zustand Neuware
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Buch | Hardcover (2025)
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CHF 69,85