most citedCollaborative Feature Learning for Fine-grained Facial Forgery Detection and Segmentation

2 citations · 3 across the 12 of their papers we have counts for

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cs.CV2024

CELLO: Causal Evaluation of Large Vision-Language Models

Meiqi Chen, Bo Peng, Yan Zhang +1

Causal reasoning is fundamental to human intelligence and crucial for effective decision-making in real-world environments. Despite recent advancements in large vision-language mod…

cs.CV2024

Counterfactual Explanations for Face Forgery Detection via Adversarial Removal of Artifacts

Yang Li, Songlin Yang, Wei Wang +3

Highly realistic AI generated face forgeries known as deepfakes have raised serious social concerns. Although DNN-based face forgery detection models have achieved good performance…

cs.CV2024

Artifact Feature Purification for Cross-domain Detection of AI-generated Images

Zheling Meng, Bo Peng, Jing Dong +1

In the era of AIGC, the fast development of visual content generation technologies, such as diffusion models, bring potential security risks to our society. Existing generated imag…

cs.CV2023

Rethinking Superpixel Segmentation from Biologically Inspired Mechanisms

Tingyu Zhao, Bo Peng, Yuan Sun +3

Recently, advancements in deep learning-based superpixel segmentation methods have brought about improvements in both the efficiency and the performance of segmentation. However, a…

cs.CV20232 cited

Collaborative Feature Learning for Fine-grained Facial Forgery Detection and Segmentation

Weinan Guan, Wei Wang, Jing Dong +2

Detecting maliciously falsified facial images and videos has attracted extensive attention from digital-forensics and computer-vision communities. An important topic in manipulatio…

cs.CV2023

Learning Invariant Representation via Contrastive Feature Alignment for Clutter Robust SAR Target Recognition

Bowen Peng, Jianyue Xie, Bo Peng +1

The deep neural networks (DNNs) have freed the synthetic aperture radar automatic target recognition (SAR ATR) from expertise-based feature designing and demonstrated superiority o…