Hermit 发表于 2025-3-21 19:15:21
书目名称Computer Vision – ECCV 2024影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0242329<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/2024/ifr/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0242329<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/2024/atr/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0242329<br><br> <br><br>书目名称Computer Vision – ECCV 2024读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0242329<br><br> <br><br>承认 发表于 2025-3-21 22:40:05
,Enhanced Sparsification via Stimulative Training,press the importance of dropped weights, which is regarded as the suppressed sparsification paradigm. However, this paradigm inactivates the dropped parts of networks causing capacity damage before pruning, thereby leading to performance degradation. To alleviate this issue, we first study and revea欲望 发表于 2025-3-22 01:26:29
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PapMOT: Exploring Adversarial Patch Attack Against Multiple Object Tracking,heir respective identities across successive frames. Despite significant progress made in multiple object tracking (MOT), recent studies have revealed the vulnerability of existing MOT methods to adversarial attacks. Nevertheless, all of these attacks belong to digital attacks that inject pixel-leveMusket 发表于 2025-3-23 03:46:49
,HiDiffusion: Unlocking Higher-Resolution Creativity and Efficiency in Pretrained Diffusion Models,n models will encounter unreasonable object duplication and exponentially increase the generation time. In this paper, we discover that object duplication arises from feature duplication in the deep blocks of the U-Net. Concurrently, We pinpoint the extended generation times to self-attention redundPulmonary-Veins 发表于 2025-3-23 05:35:51
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