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Found 3 papers, 1 papers with code
Block shuffling learning for Deepfake Detection
Finally, we restore the spatial layout of the blocks to capture the semantic associations among them.
A Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting
In this paper, a novel Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting (MFCC) is proposed, which utilizes an image fusion network architecture to fuse images from the visible and thermal infrared image, and a crowd counting network architecture to estimate the density map.
Real-centric Consistency Learning for Deepfake Detection
Essentially, the target of deepfake detection problem is to represent natural faces and fake faces at the representation space discriminatively, and it reminds us whether we could optimize the feature extraction procedure at the representation space through constraining intra-class consistence and inter-class inconsistence to bring the intra-class representations close and push the inter-class representations apart?
