Full Description
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.
Contents
.- Landmark-Based Screening: Femoral Head Coverage and Graf Classification
in Infant Developmental Dysplasia of the Hip.
.- MVTN: A Multiscale Video Transformer Network for Hand Gesture Recognition.
.- One-Shot Image Restoration.
.- Medical Image Segmentation with SAM-generated Annotations.
.- Manipulating and Mitigating Generative Model Biases without Retraining.
.- Fake or JPEG? Revealing Common Biases in Generated Image Detection
Datasets.
.- Generated Bias: Auditing Internal Bias Dynamics of Text-To-Image Generative
Models.
.- A semiotic methodology for assessing the compositional effectiveness of generative
text-to-image models (Midjourney and DALLoE).
.- A Framework for Critical Evaluation of Text-to-Image Models: Integrating
Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering.
.- Civiverse: A Dataset for Analyzing User Engagement with Open-Source
TTI-Models.
.- Exploring the Boundaries of Content Moderation in Text-to-Image Generation.
.- Rethinking HTG Evaluation: Bridging Generation and Recognition.
.- Evaluation Framework for Feedback Generation Methods in Skeletal Movement
Assessment.
.- FaceOracle: Chat with a Face Image Oracle.
.- Makeup-Guided Facial Privacy Protection via Untrained Neural Network
Priors.
.- How to Squeeze An Explanation Out of Your Model.
.- How were you created? Explaining synthetic face images generated by diffusion
models.
.- Frequency Matters: Explaining Biases of Face Recognition in the Frequency
Domain.
.- How green is continual learning, really? Analyzing the energy consumption
in continual training of vision foundation models.
.- Architecture-Agnostic Unsupervised Gradient Regularization For
Parameter-Efficient Transfer Learning.
.- Foundation Model or Finetune? Evaluation of few-shot semantic segmentation
for river pollution.
.- Personalizing Multimodal Large Language Models for Image Captioning: An
Experimental Analysis.
.- Improved Baselines for Data-efficient Perceptual Augmentation of LLMs.
.- Watt for What: Rethinking Deep Learning's Energy-Performance Relationship.
