# Skeleton-Based Human Activity Recognition on NTU RGB+D Source: [Skeleton-Based Human Activity Recognition on NTU RGB+D]() Collection index: [llms.txt]() Data updated: 2026-04-16T07:13:28.871Z Evaluation of skeleton-based human activity recognition models on the NTU RGB+D dataset, focusing on qualitative aspects such as interpretability, model complexity, and real-time suitability. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Skeleton-Based Human Activity Recognition | | Dataset (including any stated split) | NTU RGB+D | | Metric | Interpretability | | Unit | OTHER | | Direction | Higher is better | | Results loaded | 0 of 0 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Interpretability](): Higher is better; unit: OTHER. - [Model Complexity](): Lower is better; unit: SIZE. - [Inference Latency](): Lower is better; unit: TIME. ## Recorded results | Method | Interpretability | Result date | Report paper | | --- | --- | --- | --- | Page 1 of 1. This is an index page, not the full collection.