Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model
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Abstract (arXiv)
We introduce the first benchmark for a new problem --- recognizing human action adverbs (HAA): "Adverbs Describing Human Actions" (ADHA). This is the first step for computer vision to change over from pattern recognition to real AI. We demonstrate some key features of ADHA: a semantically complete set of adverbs describing human actions, a set of common, describable human actions, and an exhaustive labeling of simultaneously emerging actions in each video. We commit an in-depth analysis on the implementation of current effective models in action recognition and image captioning on adverb recognition, and the results show that such methods are unsatisfactory. Moreover, we propose a novel three-stream hybrid model to deal the HAA problem, which achieves a better result.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Feb 2018.
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Citing papers per year: 2022: 2; 2023: 2.
4 papers.
- 2022AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Timecited by 199
- 2023Learning Action Changes by Measuring Verb-Adverb Textual Relationshipscited by 8
- 2022How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbscited by 0
- 2023Reasoning over the Behaviour of Objects in Video-Clips for Adverb-Type Recognitioncited by 0
- 2023Reasoning over the Behaviour of Objects in Video-Clips for Adverb-Type Recognition9 Jul 2023
- 2023Learning Action Changes by Measuring Verb-Adverb Textual Relationships27 Mar 2023
- 2022AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time7 Nov 2022
- 2022How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs23 Mar 2022