Modality Mixer for Multi-modal Action Recognition
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Abstract (arXiv)
In multi-modal action recognition, it is important to consider not only the complementary nature of different modalities but also global action content. In this paper, we propose a novel network, named Modality Mixer (M-Mixer) network, to leverage complementary information across modalities and temporal context of an action for multi-modal action recognition. We also introduce a simple yet effective recurrent unit, called Multi-modal Contextualization Unit (MCU), which is a core component of M-Mixer. Our MCU temporally encodes a sequence of one modality (e.g., RGB) with action content features of other modalities (e.g., depth, IR). This process encourages M-Mixer to exploit global action content and also to supplement complementary information of other modalities. As a result, our proposed method outperforms state-of-the-art methods on NTU RGB+D 60, NTU RGB+D 120, and NW-UCLA datasets. Moreover, we demonstrate the effectiveness of M-Mixer by conducting comprehensive ablation studies.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 36 of its 43 references that are in the map. First posted on arXiv 24 Aug 2022.
Builds on
36 of 43 references.
References · 36
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24 more
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Built on by
Citing papers per year: 2023: 4; 2024: 2; 2025: 2; 2026: 1.
9 papers.
- 2023Audio-Visual Glance Network for Efficient Video Recognitioncited by 4
- 2023Multi-stage Factorized Spatio-Temporal Representation for RGB-D Action and Gesture Recognitioncited by 1
- 2024Spatio-Temporal Proximity-Aware Dual-Path Model for Panoramic Activity Recognitioncited by 1
- 2024Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrievalcited by 1
- 2023Sketch-based Video Object Localizationcited by 0
- 2023Modality Mixer Exploiting Complementary Information for Multi-modal Action Recognitioncited by 0
- 2025Semi-Supervised Audio-Visual Video Action Recognition with Audio Source Localization Guided Mixupcited by 0
- 2025Solution for 8th Competition on Affective & Behavior Analysis in-the-wildcited by 0
- 2026Multi-modal Video Representation Alignment for Robust Self-supervised Driver Distraction Detectioncited by 0
- 2026Multi-modal Video Representation Alignment for Robust Self-supervised Driver Distraction Detection1 Jun 2026
- 2025Solution for 8th Competition on Affective & Behavior Analysis in-the-wild14 Mar 2025
- 2025Semi-Supervised Audio-Visual Video Action Recognition with Audio Source Localization Guided Mixup4 Mar 2025
- 2024Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrieval2 Jul 2024
- 2024Spatio-Temporal Proximity-Aware Dual-Path Model for Panoramic Activity Recognition21 Mar 2024
- 2023Modality Mixer Exploiting Complementary Information for Multi-modal Action Recognition21 Nov 2023
- 2023Multi-stage Factorized Spatio-Temporal Representation for RGB-D Action and Gesture Recognition23 Aug 2023
- 2023Audio-Visual Glance Network for Efficient Video Recognition18 Aug 2023
- 2023Sketch-based Video Object Localization2 Apr 2023