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Pros and Cons of Weight Pruning for Out-of-Distribution Detection: An Empirical Survey.

, , , , , and . IJCNN, page 1-10. IEEE, (2023)

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Adversarial Mask: Real-World Adversarial Attack Against Face Recognition Models., , , and . CoRR, (2021)The Translucent Patch: A Physical and Universal Attack on Object Detectors., , , and . CoRR, (2020)Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Models., , , and . ECML/PKDD (3), volume 13715 of Lecture Notes in Computer Science, page 304-320. Springer, (2022)The Translucent Patch: A Physical and Universal Attack on Object Detectors., , , and . CVPR, page 15232-15241. Computer Vision Foundation / IEEE, (2021)QuantAttack: Exploiting Dynamic Quantization to Attack Vision Transformers., , , and . CoRR, (2023)Pros and Cons of Weight Pruning for Out-of-Distribution Detection: An Empirical Survey., , , , , and . IJCNN, page 1-10. IEEE, (2023)YolOOD: Utilizing Object Detection Concepts for Out-of-Distribution Detection., , , , , , and . CoRR, (2022)Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors., , , , and . WACV, page 4560-4569. IEEE, (2023)Denial-of-Service Attack on Object Detection Model Using Universal Adversarial Perturbation., , , , and . CoRR, (2022)DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers., , , , and . CoRR, (2024)