Taylor
发表于 2025-3-21 16:37:31
书目名称Computer Vision – ECCV 2020影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0234226<br><br> <br><br>书目名称Computer Vision – ECCV 2020读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0234226<br><br> <br><br>
Indolent
发表于 2025-3-21 21:52:21
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字形刻痕
发表于 2025-3-22 01:11:00
Dual Adversarial Network: Toward Real-World Noise Removal and Noise Generation,ates the research of noise generation, aiming at synthesizing more clean-noisy image pairs to facilitate the training of deep denoisers. In this work, we propose a novel unified framework to simultaneously deal with the noise removal and noise generation tasks. Instead of only inferring the posterio
反对
发表于 2025-3-22 06:10:36
Linguistic Structure Guided Context Modeling for Referring Image Segmentation,ence is crucial to distinguish the referent from the background. Existing methods either insufficiently or redundantly model the multimodal context. To tackle this problem, we propose a “gather-propagate-distribute” scheme to model multimodal context by cross-modal interaction and implement this sch
incision
发表于 2025-3-22 12:35:11
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Self-Help-Group
发表于 2025-3-22 15:38:22
Robust Re-Identification by Multiple Views Knowledge Distillation,a large drop in performance for single image queries (e.g., Image-To-Video setting). Recent works address this severe degradation by transferring . from a Video-based network to an Image-based one. In this work, we devise a training strategy that allows the transfer of a superior knowledge, arising
Self-Help-Group
发表于 2025-3-22 18:47:13
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拥挤前
发表于 2025-3-23 01:02:50
,RhyRNN: Rhythmic RNN for Recognizing Events in Long and Complex Videos,ains a challenge. One particular reason is that events in long and complex videos can consist of multiple heterogeneous sub-activities (in terms of rhythms, activity variants, composition order, etc.) within quite a long period. This fact brings about two main difficulties: excessive/varying length
SPALL
发表于 2025-3-23 04:42:22
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过份好问
发表于 2025-3-23 07:20:54
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning,o existing counting models that directly output count values, we divide one-step estimation into a sequence of much easier and more tractable sub-decision problems. Such sequential decision nature corresponds exactly to a physical process in reality—scale weighing. Inspired by scale weighing, we pro