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cs.CV2026

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…

cs.CV2025

DDL: A Large-Scale Datasets 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…

cs.CV2025

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,…

cs.CV2025

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…

cs.CV2024

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…