我在争斗志
发表于 2025-3-21 17:05:38
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Anhydrous
发表于 2025-3-22 00:15:57
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坚毅
发表于 2025-3-22 01:07:52
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arousal
发表于 2025-3-22 07:03:17
Rainer Gmehlich,Cliff Joneso achieve adversarial goals at test time. Although existing poisoning techniques prove to be effective in various scenarios, they rely on certain assumptions on the adversary knowledge and capability to ensure efficacy, which may be unrealistic in practice. This paper presents a new, practical targe
Confess
发表于 2025-3-22 09:57:52
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Suggestions
发表于 2025-3-22 16:38:29
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Palate
发表于 2025-3-22 17:43:30
Sebastian Wieczorek,Vitaly Kozyura,Wei Wei,Andreas Roth,Alin Stefanescu the Trojan attack (or poisoning backdoor attack). The lack of robustness of DNNs against Trojan attacks could significantly harm real-life machine learning (ML) systems in downstream applications, therefore posing widespread concern to their trustworthiness. In this paper, we study the problem of t
inchoate
发表于 2025-3-23 01:01:22
Aryldo G. Russo Jr.ned control over the generative process has lagged behind. If this new technology is to find practical uses, we need to achieve a level of control over generative networks which, without sacrificing realism, is on par with that seen in computer graphics and character animation. To this end we propos
砍伐
发表于 2025-3-23 02:04:04
Alex Hill,Jose Reis,Paulo Carvalhogning specific data augmentation methods for individual architectures. In this work, we present the first attempt to automate the design of data augmentation policies for 3D object detection. We introduce the Progressive Population Based Augmentation (PPBA) algorithm, which learns to optimize augmen
竖琴
发表于 2025-3-23 05:56:09
Stephen Wright,Kerstin Edererent HOI categories has similar visual characteristics, while ignoring the diverse semantic meanings of the verb. To address this issue, in this paper, we propose a novel Polysemy Deciphering Network (PD-Net), which decodes the visual polysemy of verbs for HOI detection in three ways. First, PD-Net