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Found 2 papers, 1 papers with code
Improving Diffusion-Based Generative Models via Approximated Optimal Transport
Our approach aims to approximate and integrate optimal transport into the training process, significantly enhancing the ability of diffusion models to estimate the denoiser outputs accurately.
Ranked #4 on
Image Generation
on CIFAR-10
Diffusion-Stego: Training-free Diffusion Generative Steganography via Message Projection
Diffusion-Stego achieved a high capacity of messages (3. 0 bpp of binary messages with 98% accuracy, and 6. 0 bpp with 90% accuracy) as well as high quality (with a FID score of 2. 77 for 1. 0 bpp on the FFHQ 64$\times$64 dataset) that makes it challenging to distinguish from real images in the PNG format.
