{"url":"/dataset/lrd","name":"LRD","full_name":"Low-Light Raw Denoising Dataset","description_markdown":"We collected a new low-light raw denoising (LRD) dataset for training and benchmarking. In contrast to the SID dataset, which sets a fixed exposure time to capture long and short exposure images, we captured long and short exposure images based on the exposure value (EV). Motivated by multi-exposure image fusion, the exposure value for long exposure images was set to 0, and the exposure value for short exposure was set to the commonly used parameters -1, -2, and -3. The dataset is designed for application to low-light raw image denoising and low-light raw image synthesis. The dataset contains both indoor and outdoor scenes. For each scene instance, we first captured a long-exposure image at ISO 100 to get a noise-free reference image. Then we captured multiple short-exposure images using different ISO levels and EVs, with a 1-2 second interval between subsequent images to wait for the sensor to cool down, thus avoiding unexpected noise introduced by sensor heating.","description_withheld":null,"homepage":"","introduced_date":"2023-07-31","introduced_date_note":null,"introduced_by":{"paper":"/paper/towards-general-low-light-raw-noise-synthesis","title":"Towards General Low-Light Raw Noise Synthesis and Modeling","first_author":"Feng Zhang","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["LRD"],"data_loaders":[],"num_papers_in_archive":6,"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."}