Computer vision - ECCV 2024 Workshop...
European Conference on Computer Vision (2024 :)

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  • Computer vision - ECCV 2024 Workshops = Milan, Italy, September 29-October 4, 2024 : proceedings.. Part XX /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Computer vision - ECCV 2024 Workshops/ edited by Alessio Del Bue ... [et al.].
    其他題名: Milan, Italy, September 29-October 4, 2024 : proceedings.
    其他題名: ECCV 2024 Workshops
    其他作者: Del Bue, Alessio.
    團體作者: European Conference on Computer Vision
    出版者: Cham :Springer Nature Switzerland : : 2025.,
    面頁冊數: lv, 420 p. :ill. (some col.), digital ;24 cm.
    內容註: TONO: a synthetic dataset for face image compliance to ISO/ICAO standard. -- mproving Post-Earthquake Crack Detection using Semi-Synthetic Gener ated Images. -- DiffAugment: Diffusion based Long-Tailed Visual Relationship Recognition. -- Neural Transcoding Vision Transformers for EEG-to-fMRI Synthesis. -- RoCOCO: Robustness Benchmark of MS-COCO to Stress-test Image-Text Matching Models. -- NeRFmentation: NeRF-based Augmentation for Monocular Depth Estima tion. -- Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition. -- Time-Resolved MNIST Dataset for Single-Photon Recognition. -- NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Hu man Pose Estimation in Top-View Fisheye Images. -- Training and Benchmarking Leukocyte Sub-types Classification Methods with Synthetic Images. -- DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance Scaling. -- Contextual Knowledge Pursuit for Faithful Visual Synthesis. -- SurgicaL-CD: Generating Surgical Images via Unpaired Image Translation with Latent Consistency Diffusion Models. -- Diffusion-based Synthetic Dataset Generation for Egocentric 3D Human Pose Estimation. -- BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabil ities in Pretrained Diffusion Models. -- A CycleGAN Model to Synthesize Missing and Unpaired MRI Sequences for Under-Represented Multiple Sclerosis Lesions. -- The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognition. -- DreamTexture: High-Fidelity Synthetic 3D Data Generation through De coupled Geometry and Texture Synthesis. -- Control+Shift: Generating Controllable Distribution Shifts. -- Comparative Analysis of Synthetic and Real Melanoma Images in AI-Driven Diagnosis. -- How Knowledge Distillation Mitigates the Synthetic Gap in Fair Face Recog nition. -- Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization. -- FABRIC: Personalizing Diffusion Models with Iterative Feedback. -- TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection.
    Contained By: Springer Nature eBook
    標題: Computer vision - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-91907-7
    ISBN: 9783031919077
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