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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: Philanthropist
41#
發(fā)表于 2025-3-28 16:34:07 | 只看該作者
,Deep Cost Ray Fusion for?Sparse Depth Video Completion,ramework consistently outperforms or rivals state-of-the-art approaches on diverse indoor and outdoor datasets, including the KITTI Depth Completion benchmark, VOID Depth Completion benchmark, and ScanNetV2 dataset, using much fewer network parameters.
42#
發(fā)表于 2025-3-28 22:13:36 | 只看該作者
43#
發(fā)表于 2025-3-29 01:17:30 | 只看該作者
44#
發(fā)表于 2025-3-29 05:05:49 | 只看該作者
45#
發(fā)表于 2025-3-29 10:37:18 | 只看該作者
,Exploring Guided Sampling of?Conditional GANs,hat generative adversarial networks (GANs) can also benefit from guided sampling, not even requiring to pre-prepare a classifier (.., classifier guidance) or learn an unconditional counterpart (.., classifier-free guidance) as in diffusion models. Inspired by the organized latent space in GANs, we m
46#
發(fā)表于 2025-3-29 14:14:03 | 只看該作者
,MotionChain: Conversational Motion Controllers via?Multimodal Prompts,ver, this proficiency remains largely unexplored in other multimodal generative models, particularly in human motion models. By integrating multi-turn conversations in controlling continuous virtual human movements,generative human motion models can achieve an intuitive and step-by-step process of h
47#
發(fā)表于 2025-3-29 18:13:23 | 只看該作者
,Idempotent Unsupervised Representation Learning for?Skeleton-Based Action Recognition,ion recognition, the features obtained from existing pre-trained generative methods contain redundant information unrelated to recognition, which contradicts the nature of the skeleton’s spatially sparse and temporally consistent properties, leading to undesirable performance. To address this challe
48#
發(fā)表于 2025-3-29 22:57:16 | 只看該作者
49#
發(fā)表于 2025-3-30 01:41:40 | 只看該作者
50#
發(fā)表于 2025-3-30 05:34:36 | 只看該作者
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