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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.CV2025

Robust Multimodal Learning via Cross-Modal Proxy Tokens

Md Kaykobad Reza, Ameya Patil, Mashhour Solh +1

Multimodal models often experience a significant performance drop when one or more modalities are missing during inference. To address this challenge, we propose a simple yet effec…

cs.CV2025

EigenScore: OOD Detection using Covariance in Diffusion Models

Shirin Shoushtari, Yi Wang, Xiao Shi +2

Out-of-distribution (OOD) detection is critical for the safe deployment of machine learning systems in safety-sensitive domains. Diffusion models have recently emerged as powerful…

cs.CV2025

VOccl3D: A Video Benchmark Dataset for 3D Human Pose and Shape Estimation under real Occlusions

Yash Garg, Saketh Bachu, Arindam Dutta +5

Human pose and shape (HPS) estimation methods have been extensively studied, with many demonstrating high zero-shot performance on in-the-wild images and videos. However, these met…

cs.CV2025

Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models

Shirin Shoushtari, Edward P. Chandler, Yuanhao Wang +2

Diffusion models are widely used as priors in imaging inverse problems. However, their performance often degrades under distribution shifts between the training and test-time image…

cs.CV2025

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,…