# Zero-Shot Activity Recognition with Verb Attribute Induction

arXiv: https://arxiv.org/abs/1707.09468 · HTML: https://mlsanity.com/paper/1707.09468/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2017.

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

- [Elaborative Rehearsal for Zero-shot Action Recognition](https://mlsanity.com/paper/2108.02833/) (2021)
- [Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization](https://mlsanity.com/paper/2302.00624/) (2023)
- [PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World](https://mlsanity.com/paper/2106.00188/) (2021)
- [MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge](https://mlsanity.com/paper/2303.08914/) (2023)
- [Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data](https://mlsanity.com/paper/2310.05010/) (2023)
- [Language-based Action Concept Spaces Improve Video Self-Supervised Learning](https://mlsanity.com/paper/2307.10922/) (2023)
- [C2C: Component-to-Composition Learning for Zero-Shot Compositional Action Recognition](https://mlsanity.com/paper/2407.06113/) (2024)
- [Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text](https://mlsanity.com/paper/2112.00800/) (2021)
- [Text-Enhanced Zero-Shot Action Recognition: A training-free approach](https://mlsanity.com/paper/2408.16412/) (2024)
- [Bootstrap Your Own Views: Masked Ego-Exo Modeling for Fine-grained View-invariant Video Representations](https://mlsanity.com/paper/2503.19706/) (2025)
- [A Kind Introduction to Lexical and Grammatical Aspect, with a Survey of Computational Approaches](https://mlsanity.com/paper/2208.09012/) (2022)
- [TEST-V: TEst-time Support-set Tuning for Zero-shot Video Classification](https://mlsanity.com/paper/2502.00426/) (2025)
- [Language as a Label: Zero-Shot Multimodal Classification of Everyday Postures under Data Scarcity](https://mlsanity.com/paper/2510.13364/) (2025)
- [How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs](https://mlsanity.com/paper/2203.12344/) (2022)
- ["Filling the Blanks'': Identifying Micro-activities that Compose Complex Human Activities of Daily Living](https://mlsanity.com/paper/2306.13149/) (2023)

## Abstract (arXiv)

In this paper, we investigate large-scale zero-shot activity recognition by modeling the visual and linguistic attributes of action verbs. For example, the verb "salute" has several properties, such as being a light movement, a social act, and short in duration. We use these attributes as the internal mapping between visual and textual representations to reason about a previously unseen action. In contrast to much prior work that assumes access to gold standard attributes for zero-shot classes and focuses primarily on object attributes, our model uniquely learns to infer action attributes from dictionary definitions and distributed word representations. Experimental results confirm that action attributes inferred from language can provide a predictive signal for zero-shot prediction of previously unseen activities.