Search Results for author: Harry Cheng

Found 7 papers, 3 papers with code

Diffusion Facial Forgery Detection

1 code implementation29 Jan 2024 Harry Cheng, Yangyang Guo, Tianyi Wang, Liqiang Nie, Mohan Kankanhalli

In particular, this dataset leverages 30, 000 carefully collected textual and visual prompts, ensuring the synthesis of images with both high fidelity and semantic consistency.

Image Generation

Robust Identity Perceptual Watermark Against Deepfake Face Swapping

no code implementations2 Nov 2023 Tianyi Wang, Mengxiao Huang, Harry Cheng, Bin Ma, Yinglong Wang

Falsification and source tracing are accomplished by justifying the consistency between the content-matched identity perceptual watermark and the recovered robust watermark from the image.

Face Swapping

Sample Less, Learn More: Efficient Action Recognition via Frame Feature Restoration

1 code implementation27 Jul 2023 Harry Cheng, Yangyang Guo, Liqiang Nie, Zhiyong Cheng, Mohan Kankanhalli

Training an effective video action recognition model poses significant computational challenges, particularly under limited resource budgets.

Action Recognition Temporal Action Localization

Towards Generalizable Deepfake Detection by Primary Region Regularization

no code implementations24 Jul 2023 Harry Cheng, Yangyang Guo, Tianyi Wang, Liqiang Nie, Mohan Kankanhalli

The existing deepfake detection methods have reached a bottleneck in generalizing to unseen forgeries and manipulation approaches.

DeepFake Detection Face Swapping

Deep Convolutional Pooling Transformer for Deepfake Detection

no code implementations12 Sep 2022 Tianyi Wang, Harry Cheng, Kam Pui Chow, Liqiang Nie

Most existing deep learning methods mainly focus on local features and relations within the face image using convolutional neural networks as a backbone.

DeepFake Detection Face Swapping +1

Voice-Face Homogeneity Tells Deepfake

no code implementations4 Mar 2022 Harry Cheng, Yangyang Guo, Tianyi Wang, Qi Li, Xiaojun Chang, Liqiang Nie

To this end, a voice-face matching method is devised to measure the matching degree of these two.

On Modality Bias Recognition and Reduction

1 code implementation25 Feb 2022 Yangyang Guo, Liqiang Nie, Harry Cheng, Zhiyong Cheng, Mohan Kankanhalli, Alberto del Bimbo

From the results on four datasets regarding the above three tasks, our method yields remarkable performance improvements compared with the baselines, demonstrating its superiority on reducing the modality bias problem.

Action Recognition Multi-modal Classification +3

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