# Joint Skeletal and Semantic Embedding Loss for Micro-gesture Classification

arXiv: https://arxiv.org/abs/2307.10624 · HTML: https://mlsanity.com/paper/2307.10624/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 17 references that are in the map.
- First posted on arXiv 20 Jul 2023.

## Builds on (most cited first, 10 of 10)

- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition](https://mlsanity.com/paper/1801.07455/) (2018)
- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition](https://mlsanity.com/paper/2107.12213/) (2021)
- [Revisiting Skeleton-based Action Recognition](https://mlsanity.com/paper/2104.13586/) (2021)
- [Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks](https://mlsanity.com/paper/1912.06971/) (2019)
- [PYSKL: Towards Good Practices for Skeleton Action Recognition](https://mlsanity.com/paper/2205.09443/) (2022)
- [iMiGUE: An Identity-free Video Dataset for Micro-Gesture Understanding and Emotion Analysis](https://mlsanity.com/paper/2107.00285/) (2021)
- [DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition](https://mlsanity.com/paper/2210.05895/) (2022)
- [Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss](https://mlsanity.com/paper/2010.16396/) (2020)

## Built on by (most cited first, 25 of 25)

- [Prototypical Calibrating Ambiguous Samples for Micro-Action Recognition](https://mlsanity.com/paper/2412.14719/) (2024)
- [MMAD: Multi-label Micro-Action Detection in Videos](https://mlsanity.com/paper/2407.05311/) (2024)
- [Micro-gesture Online Recognition using Learnable Query Points](https://mlsanity.com/paper/2407.04490/) (2024)
- [Prototype Learning for Micro-gesture Classification](https://mlsanity.com/paper/2408.03097/) (2024)
- [Data Augmentation for Human Behavior Analysis in Multi-Person Conversations](https://mlsanity.com/paper/2308.01526/) (2023)
- [MM-Gesture: Towards Precise Micro-Gesture Recognition through Multimodal Fusion](https://mlsanity.com/paper/2507.08344/) (2025)
- [Online Micro-gesture Recognition Using Data Augmentation and Spatial-Temporal Attention](https://mlsanity.com/paper/2507.09512/) (2025)
- [Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition](https://mlsanity.com/paper/2507.21977/) (2025)
- [Exploiting Ensemble Learning for Cross-View Isolated Sign Language Recognition](https://mlsanity.com/paper/2502.02196/) (2025)
- [MA-Bench: Towards Fine-grained Micro-Action Understanding](https://mlsanity.com/paper/2603.26586/) (2026)
- [Towards Fine-Grained Emotion Understanding via Skeleton-Based Micro-Gesture Recognition](https://mlsanity.com/paper/2506.12848/) (2025)
- [Spatial-Temporal Decoupled Adapter for Micro-gesture Online Recognition](https://mlsanity.com/paper/2606.07355/) (2026)
- [Self-supervised Learning Matters: A Simple Ensemble Solution for Micro-Gesture Recognition](https://mlsanity.com/paper/2606.09261/) (2026)
- [Rethinking the Role of Feature Engineering and Learning Strategies in Few-Shot Hidden Emotion Recognition](https://mlsanity.com/paper/2606.31249/) (2026)
- [Text-guided Fine-Grained Video Anomaly Understanding](https://mlsanity.com/paper/2511.00524/) (2025)
- [MAC 2026: Advancing Micro-Action Analysis Towards Fine-Grained Understanding](https://mlsanity.com/paper/2607.16284/) (2026)
- [MSF-Mamba: Motion-aware State Fusion Mamba for Efficient Micro-Gesture Recognition](https://mlsanity.com/paper/2510.10478/) (2025)
- [Exploiting Diverse Feature for Multimodal Sentiment Analysis](https://mlsanity.com/paper/2308.13421/) (2023)
- [FG-SGL: Fine-Grained Semantic Guidance Learning via Motion Process Decomposition for Micro-Gesture Recognition](https://mlsanity.com/paper/2603.16269/) (2026)
- [Micro-DualNet: Dual-Path Spatio-Temporal Network for Micro-Action Recognition](https://mlsanity.com/paper/2604.21011/) (2026)
- [Motion Reinforces Appearance: RGB-Skeleton Gated Residual Fusion for Micro-Gesture Online Recognition](https://mlsanity.com/paper/2606.11645/) (2026)
- [A Multi-Modal Framework with Cross-Subject Pseudo-Labeling and Semantic Alignment for Micro-Gesture Recognition](https://mlsanity.com/paper/2606.13030/) (2026)
- [GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs](https://mlsanity.com/paper/2607.16322/) (2026)
- [Recognition-Conditioned Reasoning: A Training-Free Multimodal-LLM Pipeline for Fine-Grained Micro-Action Understanding](https://mlsanity.com/paper/2608.21022/) (2026)
- [SoftRerank: Hierarchical Soft Fusion with Candidate-Label Reranking for Long-Tailed Micro-Action Recognition](https://mlsanity.com/paper/2609.08221/) (2026)

## Abstract (arXiv)

In this paper, we briefly introduce the solution of our team HFUT-VUT for the Micros-gesture Classification in the MiGA challenge at IJCAI 2023. The micro-gesture classification task aims at recognizing the action category of a given video based on the skeleton data. For this task, we propose a 3D-CNNs-based micro-gesture recognition network, which incorporates a skeletal and semantic embedding loss to improve action classification performance. Finally, we rank 1st in the Micro-gesture Classification Challenge, surpassing the second-place team in terms of Top-1 accuracy by 1.10%.