Titlebook: Computer Vision – ECCV 2024; 18th European Confer Aleš Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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Allergy Prevention and Therapy,atures undergo projection into a subspace via our proposed spectral regularization, with each component controlling a distinct aspect of the generated image. Beyond providing fine-grained control over the generative model, our approach achieves state-of-the-art image generation quality on benchmark datasets, including FFHQ, CelebA-HQ, and AFHQ-V2.

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Therapieplanung an virtuellen Krebspatientenule for HOI synthesis. Besides, an auto-regressive generation pipeline is also designed to obtain smooth transitions between HOI segments. Experimental results demonstrate the generalization ability to unseen object geometries and temporal compositions. Our data, codes, and models will be publicly available for research purposes.

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,: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation,eNet and FFHQ for conditional 3D generation. Moreover, it surpasses existing 3D diffusion methods in terms of inference speed, requiring no per-instance optimization. Video demos can be found on our project webpage: ..

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