{"product_id":"computer-vision-eccv-2024-workshops-9783031920882","title":"Computer Vision  ECCV 2024 Workshops","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Landmark-Based Screening: Femoral Head Coverage and Graf Classification\u003cbr\u003ein Infant Developmental Dysplasia of the Hip.\u003cbr\u003e.- MVTN: A Multiscale Video Transformer Network for Hand Gesture Recognition.\u003cbr\u003e.- One-Shot Image Restoration.\u003cbr\u003e.- Medical Image Segmentation with SAM-generated Annotations.\u003cbr\u003e.- Manipulating and Mitigating Generative Model Biases without Retraining.\u003cbr\u003e.- Fake or JPEG? Revealing Common Biases in Generated Image Detection\u003cbr\u003eDatasets.\u003cbr\u003e.- Generated Bias: Auditing Internal Bias Dynamics of Text-To-Image Generative\u003cbr\u003eModels.\u003cbr\u003e.- A semiotic methodology for assessing the compositional effectiveness of generative\u003cbr\u003etext-to-image models (Midjourney and DALLoE).\u003cbr\u003e.- A Framework for Critical Evaluation of Text-to-Image Models: Integrating\u003cbr\u003eArt Historical Analysis, Artistic Exploration, and Critical Prompt Engineering.\u003cbr\u003e.- Civiverse: A Dataset for Analyzing User Engagement with Open-Source\u003cbr\u003eTTI-Models.\u003cbr\u003e.- Exploring the Boundaries of Content Moderation in Text-to-Image Generation.\u003cbr\u003e.- Rethinking HTG Evaluation: Bridging Generation and Recognition.\u003cbr\u003e.- Evaluation Framework for Feedback Generation Methods in Skeletal Movement\u003cbr\u003eAssessment.\u003cbr\u003e.- FaceOracle: Chat with a Face Image Oracle.\u003cbr\u003e.- Makeup-Guided Facial Privacy Protection via Untrained Neural Network\u003cbr\u003ePriors.\u003cbr\u003e.- How to Squeeze An Explanation Out of Your Model.\u003cbr\u003e.- How were you created? Explaining synthetic face images generated by diffusion\u003cbr\u003emodels.\u003cbr\u003e.- Frequency Matters: Explaining Biases of Face Recognition in the Frequency\u003cbr\u003eDomain.\u003cbr\u003e.- How green is continual learning, really? Analyzing the energy consumption\u003cbr\u003ein continual training of vision foundation models.\u003cbr\u003e.- Architecture-Agnostic Unsupervised Gradient Regularization For\u003cbr\u003eParameter-Efficient Transfer Learning.\u003cbr\u003e.- Foundation Model or Finetune? Evaluation of few-shot semantic segmentation\u003cbr\u003efor river pollution.\u003cbr\u003e.- Personalizing Multimodal Large Language Models for Image Captioning: An\u003cbr\u003eExperimental Analysis.\u003cbr\u003e.- Improved Baselines for Data-efficient Perceptual Augmentation of LLMs.\u003cbr\u003e.- Watt for What: Rethinking Deep Learning’s Energy-Performance Relationship.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53195480793431,"sku":"9783031920882","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/computer-vision-eccv-2024-workshops-9783031920882","provider":"Book Curl","version":"1.0","type":"link"}