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

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樓主: minutia
41#
發(fā)表于 2025-3-28 15:26:50 | 只看該作者
42#
發(fā)表于 2025-3-28 19:57:46 | 只看該作者
43#
發(fā)表于 2025-3-28 23:43:24 | 只看該作者
E. Gr?del,M. Rossetti,F. Hardering baseline, SimCLR, and accelerates convergence. Comparison against four recent contrastive and masked autoencoding-based methods for remote sensing also highlight the efficacy of our approach. Furthermore, our framework enables multimodal classification with metadata to improve the performance of
44#
發(fā)表于 2025-3-29 03:31:51 | 只看該作者
Allgemeine und spezielle Chirurgieease the texture quality while disentangling surface material from lighting. Our algorithm is significantly faster than previous text-to-texture methods, while producing high-quality and relightable textures.
45#
發(fā)表于 2025-3-29 07:57:12 | 只看該作者
Chirurgie des praktischen Arztesr synthetic rendered partial observations from synthetic object models. The learned knowledge from synthetic data generalizes to observations of unseen objects in the real scenes, without any fine-tuning. We demonstrate this with a rich evaluation on the NOCS, Wild6D and SUN RGB-D benchmarks, showin
46#
發(fā)表于 2025-3-29 14:55:20 | 只看該作者
Allgemeine und spezielle Chirurgieage-object-attribute relations to use towards attribute recognition. Specifically, for each attribute to be recognized on an image, we measure the visual-conditioned probability of generating a short sentence encoding the attribute’s relation to objects on the image. Unlike contrastive retrieval, wh
47#
發(fā)表于 2025-3-29 16:09:15 | 只看該作者
48#
發(fā)表于 2025-3-29 23:03:25 | 只看該作者
https://doi.org/10.1007/978-3-642-96354-4ate-of-the-art performance in denoising accuracy, including open-source datasets and datasets captured in practical scenarios with low-light intensity requirements such as zebrafish blood vessels imaging.
49#
發(fā)表于 2025-3-30 01:33:10 | 只看該作者
50#
發(fā)表于 2025-3-30 06:37:42 | 只看該作者
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