# Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space

arXiv: https://arxiv.org/abs/1911.11344 · HTML: https://mlsanity.com/paper/1911.11344/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Nov 2019.

## Built on by (most cited first, 19 of 19)

- [Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition](https://mlsanity.com/paper/2101.11530/) (2021)
- [Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and Maximization](https://mlsanity.com/paper/2308.03950/) (2023)
- [Fine-Grained Side Information Guided Dual-Prompts for Zero-Shot Skeleton Action Recognition](https://mlsanity.com/paper/2404.07487/) (2024)
- [One-shot action recognition in challenging therapy scenarios](https://mlsanity.com/paper/2102.08997/) (2021)
- [Neuron: Learning Context-Aware Evolving Representations for Zero-Shot Skeleton Action Recognition](https://mlsanity.com/paper/2411.11288/) (2024)
- [Zero-Shot Aerial Object Detection with Visual Description Regularization](https://mlsanity.com/paper/2402.18233/) (2024)
- [Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition](https://mlsanity.com/paper/2309.09592/) (2023)
- [Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment](https://mlsanity.com/paper/2409.14336/) (2024)
- [An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition](https://mlsanity.com/paper/2406.00639/) (2024)
- [Domain and View-point Agnostic Hand Action Recognition](https://mlsanity.com/paper/2103.02303/) (2021)
- [Zero-Shot Skeleton-Based Action Recognition With Prototype-Guided Feature Alignment](https://mlsanity.com/paper/2507.00566/) (2025)
- [Learning by Neighbor-Aware Semantics, Deciding by Open-form Flows: Towards Robust Zero-Shot Skeleton Action Recognition](https://mlsanity.com/paper/2511.09388/) (2025)
- [SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition](https://mlsanity.com/paper/2603.29692/) (2026)
- [SCALE: Semantic- and Confidence-Aware Conditional Variational Autoencoder for Zero-shot Skeleton-based Action Recognition](https://mlsanity.com/paper/2604.02222/) (2026)
- [Automated Classification of Cybercrime Complaints using Transformer-based Language Models for Hinglish Texts](https://mlsanity.com/paper/2412.16614/) (2024)
- [Toward Universal Skeleton-Based Action Recognition across Heterogeneous Skeletons and Open Vocabularies](https://mlsanity.com/paper/2604.17013/) (2026)
- [PoseBridge: Bridging the Skeletonization Gap for Zero-Shot Skeleton-Based Action Recognition](https://mlsanity.com/paper/2605.11497/) (2026)
- [GenPrior: Unleashing Text-to-Motion Generative Priors for Zero-Shot Skeleton-based Action Recognition](https://mlsanity.com/paper/2608.02236/) (2026)
- [Zero-Shot Skeleton-Based Action Anticipation](https://mlsanity.com/paper/2608.14243/) (2026)

## Abstract (arXiv)

How does one represent an action? How does one describe an action that we have never seen before? Such questions are addressed by the Zero Shot Learning paradigm, where a model is trained on only a subset of classes and is evaluated on its ability to correctly classify an example from a class it has never seen before. In this work, we present a body pose based zero shot action recognition network and demonstrate its performance on the NTU RGB-D dataset. Our model learns to jointly encapsulate visual similarities based on pose features of the action performer as well as similarities in the natural language descriptions of the unseen action class names. We demonstrate how this pose-language semantic space encodes knowledge which allows our model to correctly predict actions not seen during training.