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cs.CV2026

ChronoLock: Protecting Videos from Unauthorized Text-to-Video Personalization

Jiaming He, Jiashu Zhang, Guanyu Hou +4

Text-to-video (T2V) diffusion models have made it increasingly easy to synthesize realistic and temporally coherent videos, while recent personalization techniques allow such model…

cs.CV2026

Semantic Router: On the Feasibility of Hijacking MLLMs via a Single Adversarial Perturbation

Changyue Li, Jiaying Li, Youliang Yuan +3

Multimodal Large Language Models (MLLMs) are increasingly deployed in stateless systems, such as autonomous driving and robotics. This paper investigates a novel threat: Semantic-A…

cs.CV2026

Spectral Defense Against Resource-Targeting Attack in 3D Gaussian Splatting

Yang Chen, Yi Yu, Jiaming He +3

Recent advances in 3D Gaussian Splatting (3DGS) deliver high-quality rendering, yet the Gaussian representation exposes a new attack surface, the resource-targeting attack. This at…

cs.CV2026

TEAR: Temporal-aware Automated Red-teaming for Text-to-Video Models

Jiaming He, Guanyu Hou, Hongwei Li +6

Text-to-Video (T2V) models are capable of synthesizing high-quality, temporally coherent dynamic video content, but the diverse generation also inherently introduces critical safet…

cs.CV2025

BadDepth: Backdoor Attacks Against Monocular Depth Estimation in the Physical World

Ji Guo, Long Zhou, Zhijin Wang +4

In recent years, deep learning-based Monocular Depth Estimation (MDE) models have been widely applied in fields such as autonomous driving and robotics. However, their vulnerabilit…

cs.CV2025

BadRefSR: Backdoor Attacks Against Reference-based Image Super Resolution

Xue Yang, Tao Chen, Lei Guo +4

Reference-based image super-resolution (RefSR) represents a promising advancement in super-resolution (SR). In contrast to single-image super-resolution (SISR), RefSR leverages an…