Diving48 is a fine-grained video action recognition dataset of competitive diving. It contains approximately 18,000 trimmed video clips spanning 48 distinct dive sequences (classes) defined by FINA rules. Each class corresponds to an unambiguous dive sequence (a combination of takeoff/dive group, flight movements such as somersaults/twists, and entry/position), so distinguishing classes requires modeling subtle, long-range temporal dynamics rather than just single-frame appearance. The dataset is widely used as a benchmark for fine-grained action classification (standard train/test splits are used in the literature) and evaluations typically report top-1 classification accuracy. Public references/hosts include the UCSD SVCL project page (dataset description) and a Hugging Face dataset entry (bkprocovid19/diving48).
No results indexed yet — be the first to submit a score.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.