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aeroblade

[CVPR2024] AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error

contourlet-cnn

An implementation of Contourlet-CNN based on PyTorch.

controlnet

Let us control diffusion models!

controlnet-v1-1-nightly

Nightly release of ControlNet 1.1

fenet

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

pnp_diffusion

Official Pytorch Implementation for “Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation” (CVPR 2023)

radam

We propose a new method named Random encoding of Aggregated Deep Activation Maps (RADAM) for feature extraction from pre-trained Deep CNNs. The technique consists of encoding the output at different depths of the CNN using a Randomized Autoencoder, producing a single image descriptor

sam

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

stable_diffusion

A latent text-to-image diffusion model