Dataset: SCLIC This dataset is released as part of the publication "Challenging Cases of Neural Image Compression: A Dataset of Visually Compelling Yet Semantically Incorrect Reconstructions," accepted at the 33rd ACM International Conference on Multimedia'25.Paper: https://fileshare.uibk.ac.at/f/bddcbc8d359742bd9a05/Appendix: https://fileshare.uibk.ac.at/f/37d4f9a33d57473ba647/ Overview The dataset is a collection of human-annotated miscompressions, collected in images compressed with different neural compression codecs at different quality settings. It consists of two CSV files sclic_annotations.csv sclic_images.csv and a collection of images provided in the following format: miscomp_uncompressed.zip(1 archive of 1563 uncompressed images) miscomp__.zip (12 archives of 1563 compressed images) There are six codecs, each with two qualities. The compressed archives contain both the compressed and the reconstructed images. (Exceptions are the codecs CDC and STF, which contain reconstructions only.) This dataset is also described using the Croissant metadata standard. See croissant.json for machine-readable metadata. Download instructions The following command downloads both CSV files and all archive files. # Create a directory for the dataset and move into it mkdir sclic_dataset && cd sclic_dataset # Download the annotation and images lists and all dataset archives from Zenodo wget -i - <