{"url":"/dataset/llnerf-dataset","name":"LLNeRF Dataset","full_name":null,"description_markdown":"**LLNeRF Dataset** is a real-world dataset as a benchmark for model learning and evaluation. To obtain real low-illumination images with real noise distributions, photos are taken at nighttime outdoor scenes or low-light indoor scenes containing diverse objects. Since the ISP operations are device dependent and the noise distributions across devices are also different, the data is collected using a mobile phone camera and a DSLR camera to enrich the diversity of the dataset.","description_withheld":null,"homepage":"https://www.whyy.site/paper/llnerf","introduced_date":"2023-07-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/lighting-up-nerf-via-unsupervised","title":"Lighting up NeRF via Unsupervised Decomposition and Enhancement","first_author":"Haoyuan Wang","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Novel View Synthesis","url":"/task/novel-view-synthesis","datasets_with_task":"/datasets/task/novel-view-synthesis"},{"name":"Low-Light Image Enhancement","url":"/task/low-light-image-enhancement","datasets_with_task":"/datasets/task/low-light-image-enhancement"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["LLNeRF Dataset"],"data_loaders":[],"num_papers_in_archive":1,"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":"2026-09-24T18:15:14+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."}