{"url":"/dataset/supercaustics","name":"SuperCaustics","full_name":null,"description_markdown":"SuperCaustics is a simulation tool made in Unreal Engine for generating massive computer vision datasets that include transparent objects.\r\n\r\nSuperCaustics is a real-time, open-source simulation of transparent objects designed for deep learning applications. SuperCaustics features extensive modules for stochastic environment creation; uses hardware ray-tracing to support caustics, dispersion, and refraction; and enables generating massive datasets with multi-modal, pixel-perfect ground truth annotations.\r\n\r\n<p align=\"center\">\r\n  <img src=\"https://github.com/MMehdiMousavi/SuperCaustics/raw/main/Assets/SuperCaustics.gif\" alt=\"drawing\" width=\"600\"/>\r\n</p>","description_withheld":null,"homepage":"https://github.com/MMehdiMousavi/SuperCaustics","introduced_date":"2021-07-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/supercaustics-real-time-open-source","title":"SuperCaustics: Real-time, open-source simulation of transparent objects for deep learning applications","first_author":"Mehdi Mousavi","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Interactive","url":"/datasets/modality/interactive"},{"name":"Environment","url":"/datasets/modality/environment"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"},{"name":"LiDAR","url":"/datasets/modality/lidar"},{"name":"Physics","url":"/datasets/modality/physics"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Depth Completion","url":"/task/depth-completion","datasets_with_task":"/datasets/task/depth-completion"},{"name":"Surface Normals Estimation","url":"/task/surface-normals-estimation","datasets_with_task":"/datasets/task/surface-normals-estimation"},{"name":"Transparent Object Depth Estimation","url":"/task/transparent-object-depth-estimation","datasets_with_task":"/datasets/task/transparent-object-depth-estimation"},{"name":"Caustics Segmentation","url":"/task/caustics-segmentation","datasets_with_task":"/datasets/task/caustics-segmentation"},{"name":"Transparent Object Detection","url":"/task/transparent-object-detection","datasets_with_task":"/datasets/task/transparent-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SuperCaustics"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}