LSUN

doi:doi:10.57702/ma9a00oc

LSUN

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

BibTex:

@dataset{Fisher_Yu_and_Ari_Seff_and_Yinda_Zhang_and_Shuran_Song_and_Thomas_Funkhouser_and_Jianxiong_Xiao_2024,
    abstract = {The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.},
    author = {Fisher Yu and Ari Seff and Yinda Zhang and Shuran Song and Thomas Funkhouser and Jianxiong Xiao},
    doi = {10.57702/ma9a00oc},
    institution = {No Organization},
    keyword = {'Bedroom Dataset', 'Bedrooms', 'Churches', 'Deep Learning', 'Deep Neural Networks', 'Generative Adversarial Networks', 'Generative Models', 'High-resolution images', 'Human Faces', 'Image Classification', 'Image Dataset', 'Image Generation', 'Image Inpainting', 'Image Recognition', 'Image Super-Resolution', 'Image Synthesis', 'Image classification', 'Initial Experiments', 'LSUN', 'Large-Scale Images', 'Object Detection', 'Object detection', 'Out-of-Distribution Detection', 'Room Images', 'Scene Images', 'Scene Understanding', 'Scene understanding', 'Scenes', 'StyleGAN', 'Synthetic Images', 'arbitrary scale', 'high-resolution images', 'image classification', 'image datasets', 'image restoration', 'image segmentation', 'image synthesis', 'indoor scenes', 'landmark detection', 'object recognition', 'outdoor scenes', 'scene generation', 'scene upsampling', 'scenes', 'semantic segmentation'},
    month = {dec},
    publisher = {TIB},
    title = {LSUN},
    url = {https://service.tib.eu/ldmservice/dataset/lsun},
    year = {2024}
}