悄悄移动 发表于 2025-3-28 14:59:55
Henry C. Fung MD,Stephen J. Forman MDNet train specific segmentation models on the individual datasets. Plenty of recent methods have been proposed to adapt the foundational Segment Anything Model (SAM) to medical image segmentation. However, they still focus on discrete representations to generate pixel-wise predictions, which are spaperimenopause 发表于 2025-3-28 18:56:16
http://reply.papertrans.cn/25/2424/242326/242326_42.pngAnticoagulants 发表于 2025-3-29 00:34:55
Der Nutzen für die Geschichtswissenschaftpearance changes, the prevailing paradigm that presents facial motions by directly modifying point appearance may lead to distortions in dynamic regions. To tackle this challenge, we introduce TalkingGaussian, a deformation-based radiance fields framework for high-fidelity talking head synthesis. Leflorid 发表于 2025-3-29 03:24:33
https://doi.org/10.1007/978-3-642-74726-7h existing Multimodal Large Language Models (MLLMs) can respond to audio-visual content, these responses are sometimes ambiguous and fail to describe specific audio-visual events. To overcome this limitation, we introduce the CAT, which enhances MLLM in three ways: 1) besides straightforwardly bridgMonotonous 发表于 2025-3-29 09:31:27
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Allokationseffizienz in der Rechtsordnung concepts (content). The separation of style and content is essential for manipulating the image’s style independently from its content, ensuring a harmonious and visually pleasing result. Achieving this separation requires a deep understanding of both the visual and semantic characteristics of imag善于骗人 发表于 2025-3-29 16:15:09
Allokationseffizienz in der Rechtsordnungus methods focus on predicting predefined object and relation categories, hence limiting their applications in the open world scenarios. With the rapid development of large multimodal models (LMMs), significant progress has been made in open-set object detection and segmentation, yet open-set relati倔强一点 发表于 2025-3-29 19:52:27
http://reply.papertrans.cn/25/2424/242326/242326_48.png漫步 发表于 2025-3-30 02:14:10
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