1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
AoE: Always-on Egocentric Human Video Collection for Embodied AI
Bowen Yang, Zishuo Li, Yang Sun +15
Embodied foundation models require large-scale, high-quality real-world interaction data for pre-training and scaling. However, existing data collection methods suffer from high in…
MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarios
Changtao Miao, Yi Zhang, Man Luo +9
Rapid advances in Artificial Intelligence Generated Content (AIGC) have enabled increasingly sophisticated face forgeries, posing a significant threat to social security. However,…
DDL: A Large-Scale Dataset for Deepfake Detection and Localization in Diversified Real-World Scenarios
Changtao Miao, Yi Zhang, Weize Gao +11
Recent advances in AIGC have exacerbated the misuse of malicious deepfake content, making the development of reliable deepfake detection methods an essential means to address this…
Inclusion 2024 Global Multimedia Deepfake Detection Challenge: Towards Multi-dimensional Face Forgery Detection
Yi Zhang, Weize Gao, Changtao Miao +10
In this paper, we present the Global Multimedia Deepfake Detection held concurrently with the Inclusion 2024. Our Multimedia Deepfake Detection aims to detect automatic image and a…
Mixture-of-Noises Enhanced Forgery-Aware Predictor for Multi-Face Manipulation Detection and Localization
Changtao Miao, Qi Chu, Tao Gong +6
With the advancement of face manipulation technology, forgery images in multi-face scenarios are gradually becoming a more complex and realistic challenge. Despite this, detection…