# One-shot action recognition in challenging therapy scenarios

arXiv: https://arxiv.org/abs/2102.08997 · HTML: https://mlsanity.com/paper/2102.08997/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 27 references that are in the map.
- First posted on arXiv 17 Feb 2021.

## Builds on (most cited first, 17 of 17)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Matching Networks for One Shot Learning](https://mlsanity.com/paper/1606.04080/) (2016)
- [WaveNet: A Generative Model for Raw Audio](https://mlsanity.com/paper/1609.03499/) (2016)
- [An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling](https://mlsanity.com/paper/1803.01271/) (2018)
- [NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding](https://mlsanity.com/paper/1905.04757/) (2019)
- [Long-term Recurrent Convolutional Networks for Visual Recognition and Description](https://mlsanity.com/paper/1411.4389/) (2014)
- [Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition](https://mlsanity.com/paper/2003.14111/) (2020)
- [Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features](https://mlsanity.com/paper/1703.02507/) (2017)
- [PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition](https://mlsanity.com/paper/1911.12409/) (2019)
- [Interpretable 3D Human Action Analysis with Temporal Convolutional Networks](https://mlsanity.com/paper/1704.04516/) (2017)
- [View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition](https://mlsanity.com/paper/1804.07453/) (2018)
- [Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates](https://mlsanity.com/paper/1706.08276/) (2017)
- [Interaction Relational Network for Mutual Action Recognition](https://mlsanity.com/paper/1910.04963/) (2019)
- [Make Skeleton-based Action Recognition Model Smaller, Faster and Better](https://mlsanity.com/paper/1907.09658/) (2019)
- [Action2Vec: A Crossmodal Embedding Approach to Action Learning](https://mlsanity.com/paper/1901.00484/) (2019)
- [Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space](https://mlsanity.com/paper/1911.11344/) (2019)
- [One-Shot-Learning Gesture Recognition using HOG-HOF Features](https://mlsanity.com/paper/1312.4190/) (2013)

## Built on by (most cited first, 15 of 15)

- [MotionBERT: A Unified Perspective on Learning Human Motion Representations](https://mlsanity.com/paper/2210.06551/) (2022)
- [Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions](https://mlsanity.com/paper/2202.11423/) (2022)
- [One-Shot Action Recognition via Multi-Scale Spatial-Temporal Skeleton Matching](https://mlsanity.com/paper/2307.07286/) (2023)
- [Taylor Videos for Action Recognition](https://mlsanity.com/paper/2402.03019/) (2024)
- [A Comprehensive Review of Few-shot Action Recognition](https://mlsanity.com/paper/2407.14744/) (2024)
- [Domain and View-point Agnostic Hand Action Recognition](https://mlsanity.com/paper/2103.02303/) (2021)
- [MoFM: A Large-Scale Human Motion Foundation Model](https://mlsanity.com/paper/2502.05432/) (2025)
- [Human Gesture and Gait Analysis for Autism Detection](https://mlsanity.com/paper/2304.08368/) (2023)
- [SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation](https://mlsanity.com/paper/2504.11749/) (2025)
- [Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder](https://mlsanity.com/paper/2409.13606/) (2024)
- [Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data](https://mlsanity.com/paper/2309.15635/) (2023)
- [Online Action Representation using Change Detection and Symbolic Programming](https://mlsanity.com/paper/2405.11511/) (2024)
- [Skeleton-based action analysis for ADHD diagnosis](https://mlsanity.com/paper/2304.09751/) (2023)
- [Skarimva: Skeleton-based Action Recognition is a Multi-view Application](https://mlsanity.com/paper/2602.23231/) (2026)
- [Fine-grained Human Motion Understanding with Language Models](https://mlsanity.com/paper/2606.20888/) (2026)

## Abstract (arXiv)

One-shot action recognition aims to recognize new action categories from a single reference example, typically referred to as the anchor example. This work presents a novel approach for one-shot action recognition in the wild that computes motion representations robust to variable kinematic conditions. One-shot action recognition is then performed by evaluating anchor and target motion representations. We also develop a set of complementary steps that boost the action recognition performance in the most challenging scenarios. Our approach is evaluated on the public NTU-120 one-shot action recognition benchmark, outperforming previous action recognition models. Besides, we evaluate our framework on a real use-case of therapy with autistic people. These recordings are particularly challenging due to high-level artifacts from the patient motion. Our results provide not only quantitative but also online qualitative measures, essential for the patient evaluation and monitoring during the actual therapy.