10 datasets found

LSUN-{cat, bedroom, church} [48] and FFHQ [25] datasets

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used pre-trained DDPMs on ImageNet 64x64, ImageNet 128x128, and LSUN 256x256.

The dataset used in the paper is the LSUN bedrooms dataset, a large-scale image dataset.

High-resolution images of bedrooms.

High-resolution images of churches.

The dataset used in the paper is a large set of real images extracted from various object categories of the LSUN dataset and 362K images generated by 20 ProGAN models.

The proposed method uses the FFHQ, AFHQ, and LSUN datasets for image generation tasks.

The LSUN Bedroom and LSUN Cat dataset is a large-scale image dataset used for training and testing the proposed approach.

The authors used three datasets: Large-scale Scene Understanding (LSUN), Imagenet-1k, and a newly assembled Faces dataset.

The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.