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BoundaryDiffusion
The dataset used in the paper for semantic control and manipulation of images using pre-trained diffusion models. -
IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated I...
IMD2020: A large-scale annotated dataset tailored for detecting manipulated images -
DEFACTO: Image and Face Manipulation Dataset
DEFACTO: Image and face manipulation dataset -
SinIR: Efficient General Image Manipulation with Single Image Reconstruction
SinIR is a reconstruction-based framework trained on a single natural image for general image manipulation. -
LDEdit: Towards Generalized Text Guided Image Manipulation via Latent Diffusi...
Open-domain image manipulation using arbitrary text prompts -
FFHQ, AFHQ-Cat, and LSUN-Church
The dataset used in the paper is a large dataset of images, including FFHQ, AFHQ-Cat, and LSUN-Church. -
COCO-Glide dataset
The COCO-Glide dataset is a dataset consisting of 512 manipulated images of 256 × 256 px, created using a single method (GLIDE). -
LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned ...
Text-guided image manipulation tasks have recently gained attention in the vision-and-language community. The GeNeVA task is a multi-turn text-conditioned image generation... -
FaceForensics++
Deepfakes have become a critical social problem, and detecting them is of utmost importance. The FaceForensics++ dataset offers fake video datasets. Most of the detection... -
MULTI-CONCEPT T2I-ZERO: TWEAKING ONLY THE TEXT EMBEDDINGS AND NOTHING ELSE
The dataset used in the paper is a text-to-image diffusion model, specifically Stable Diffusion. The authors used this model to generate images from text prompts and evaluated...
