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20202026
most citedLearning Illumination Patterns for Coded Diffraction Phase Retrieval

2 citations · 5 across the 4 of their papers we have counts for

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cs.CV2026

Modular Energy Steering for Safe Text-to-Image Generation with Foundation Models

Yaoteng Tan, Zikui Cai, M. Salman Asif

Controlling the behavior of text-to-image generative models is critical for safe and practical deployment. Existing safety approaches typically rely on model fine-tuning or curated…

cs.CV2024

Transform-Dependent Adversarial Attacks

Yaoteng Tan, Zikui Cai, M. Salman Asif

Deep networks are highly vulnerable to adversarial attacks, yet conventional attack methods utilize static adversarial perturbations that induce fixed mispredictions. In this work,…

cs.CV2023

Ensemble-based Blackbox Attacks on Dense Prediction

Zikui Cai, Yaoteng Tan, M. Salman Asif

We propose an approach for adversarial attacks on dense prediction models (such as object detectors and segmentation). It is well known that the attacks generated by a single surro…

cs.CV20222 cited

Zero-Query Transfer Attacks on Context-Aware Object Detectors

Zikui Cai, Shantanu Rane, Alejandro E. Brito +4

Adversarial attacks perturb images such that a deep neural network produces incorrect classification results. A promising approach to defend against adversarial attacks on natural…

cs.CV20211 cited

Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes

Mingjun Yin, Shasha Li, Zikui Cai +4

Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in th…