Spring
发表于 2025-3-21 17:25:06
书目名称Computer Vision – ECCV 2022影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0234274<br><br> <br><br>书目名称Computer Vision – ECCV 2022读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0234274<br><br> <br><br>
DAUNT
发表于 2025-3-21 20:37:45
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consolidate
发表于 2025-3-22 03:51:23
,AdvDO: Realistic Adversarial Attacks for Trajectory Prediction,her prediction accuracy, few study the adversarial robustness of their methods. To bridge this gap, we propose to study the adversarial robustness of data-driven trajectory prediction systems. We devise an optimization-based adversarial attack framework that leverages a carefully-designed . to gener
现实
发表于 2025-3-22 06:46:48
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Arteriography
发表于 2025-3-22 09:05:16
One Size Does NOT Fit All: Data-Adaptive Adversarial Training,ne of the most effective ways to improve the model’s adversarial robustness, it usually yields models with lower natural accuracy. In this paper, we argue that, for the attackable examples, traditional adversarial training which utilizes a fixed size perturbation ball can create adversarial examples
FOLD
发表于 2025-3-22 16:45:04
,UniCR: Universally Approximated Certified Robustness via Randomized Smoothing,ximated certified robustness (UniCR) framework, which can approximate the robustness certification of . input on . classifier against . . perturbations with noise generated by . continuous probability distribution. Compared with the state-of-the-art certified defenses, UniCR provides many significan
FOLD
发表于 2025-3-22 19:24:54
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archetype
发表于 2025-3-22 23:58:14
,Robust Network Architecture Search via Feature Distortion Restraining,domains. Most of existing methods improve model robustness from weight optimization, such as adversarial training. However, the architecture of DNNs is also a key factor to robustness, which is often neglected or underestimated. We propose Robust Network Architecture Search (RNAS) to obtain a robust
欢笑
发表于 2025-3-23 04:12:52
,SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination,ned models are released online to facilitate further research. However, it raises extensive concerns on whether these pre-trained models would leak privacy-sensitive information of their training data. Thus, in this work, we aim to answer the following questions: “Can we effectively recover private
BUDGE
发表于 2025-3-23 07:41:39
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