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发表于 2025-3-21 18:24:19
书目名称Computer Vision – ECCV 2024影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0242326<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0242326<br><br> <br><br>
Lime石灰
发表于 2025-3-21 21:29:26
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IRS
发表于 2025-3-22 03:10:17
,Label-Anticipated Event Disentanglement for Audio-Visual Video Parsing,the timeline, making identification challenging. While traditional methods usually focus on improving the early audio-visual encoders to embed more effective features, the decoding phase – crucial for final event classification, often receives less attention. We aim to advance the decoding phase and
伪造
发表于 2025-3-22 08:13:40
,High-Fidelity 3D Textured Shapes Generation by Sparse Encoding and Adversarial Decoding,nother discrepancy is the amount of training data, which undeniably affects generalization if we only use limited 3D data. To solve these, we design a 3D generation framework that maintains most of the building blocks of StableDiffusion with minimal adaptations for textured shape generation. We desi
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发表于 2025-3-22 09:46:18
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projectile
发表于 2025-3-22 14:21:37
,I-MedSAM: Implicit Medical Image Segmentation with Segment Anything,Net 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 spa
projectile
发表于 2025-3-22 17:33:14
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nostrum
发表于 2025-3-22 22:36:35
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addition
发表于 2025-3-23 01:51:23
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarioh 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 bridg
LIMN
发表于 2025-3-23 06:11:50
,Segmentation-Guided Layer-Wise Image Vectorization with Gradient Fills,capability to create vector images of clear topology, filling these primitives with gradients remains a challenge. In this paper, we propose a segmentation-guided vectorization framework to convert raster images into concise vector graphics with radial gradient fills. With the guidance of an embedde