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Produktbild: Computer Vision – ECCV 2024 Workshops
Band 15643

Computer Vision – ECCV 2024 Workshops Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXI

Aus der Reihe Lecture Notes in Computer Science

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

31.05.2025

Abbildungen

LV, 132 illus., 129 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Alessio Del Bue + weitere

Verlag

Springer

Seitenzahl

454

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

768 g

Sprache

Englisch

ISBN

978-3-031-92647-1

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

31.05.2025

Abbildungen

LV, 132 illus., 129 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

454

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

768 g

Sprache

Englisch

ISBN

978-3-031-92647-1

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

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  • Produktbild: Computer Vision – ECCV 2024 Workshops

  • FALCON: Fair Active Learning for Content Moderation.- Generalizing Fairness to Generative Language Models via Reformulation of Non-discrimination Criteria.- Beyond the Surface: A Comprehensive Analysis of Implicit Bias in Vision-Language Models.- Fairness of AI Systems in the Legal Context.- DebiasPI: Inference-time Debiasing by Prompt Iteration of a Text-to-Image Generative Model.- Fairness Under Cover: Evaluating the Impact of Occlusions on Demographic Bias in Facial Recognition.- Prompt and Prejudice.- Localization-Guided Supervision for Robust Medical Image Classification by Vision Transformers.- Top-GAP: Integrating Size Priors in CNNs for more Interpretability, Robustness, and Bias Mitigation.- Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers.- 

    An Investigation on The Position Encoding in Vision-Based Dynamics Prediction.- What could go wrong? Discovering and describing failure modes in computer vision.- Image-guided topic modeling for interpretable privacy classification.- Integrating Local and Global Interpretability for Deep Concept-Based Reasoning Models.- From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation.- Feature Contribution in Monocular Depth Estimation.- Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?.- Explanation Alignment: Quantifying the Correctness of Model Reasoning At Scale.- Detect Fake with Fake: Leveraging Synthetic Data-driven Representation

    for Synthetic Image Detection.- Incremental and Decremental Continual Learning for Privacy-preserving

    Video Recognition.- Exploring Strengths and Weaknesses of Super-Resolution Attack in Deepfake

    Detection.- Are CLIP features all you need for Universal Synthetic Image Origin Attribution?.- GLoFool: global enhancements and local perturbations to craft adversarial images.- Evolution of Detection Performance throughout the Online Lifespan of Synthetic Images.- Your diffusion model is an implicit synthetic image detector.- The Phantom Menace: Unmasking Privacy Leakages in Vision-Language

    Models.