Search Results for author:
Found 7 papers, 4 papers with code
DDAP: Dual-Domain Anti-Personalization against Text-to-Image Diffusion Models
Specifically, we have developed Spatial Perturbation Learning (SPL) by exploiting the fixed and perturbation-sensitive nature of the image encoder in personalized generation.
GM-DF: Generalized Multi-Scenario Deepfake Detection
In this paper, we elaborately investigate the generalization capacity of deepfake detection models when jointly trained on multiple face forgery detection datasets.
Selective Domain-Invariant Feature for Generalizable Deepfake Detection
To solve this problem, we proposed a novel framework Selective Domain-Invariant Feature (SDIF), which reduces the sensitivity to face forgery by fusing content features and styles.
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models
For the face forgery detection task, we evaluate GAN-based and diffusion-based data with both visual and acoustic modalities.
A brief introduction to a framework named Multilevel Guidance-Exploration Network
Human behavior anomaly detection aims to identify unusual human actions, playing a crucial role in intelligent surveillance and other areas.
QE-BEV: Query Evolution for Bird's Eye View Object Detection in Varied Contexts
The dynamic nature of real-world environments necessitates the use of dynamic query mechanisms in 3D object detection to adaptively capture and process the complex spatio-temporal relationships present in these scenes.
Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
The rapid advancements in computer vision have stimulated remarkable progress in face forgery techniques, capturing the dedicated attention of researchers committed to detecting forgeries and precisely localizing manipulated areas.
