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Multimodal Activity Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
OPERAnet: A Multimodal Activity Recognition Dataset Acquired from Radio Frequency and Vision-based Sensors
Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks
Distilling Audio-Visual Knowledge by Compositional Contrastive Learning
Multi-GAT: A Graphical Attention-based Hierarchical Multimodal Representation Learning Approach for Human Activity Recognition
HAMLET: A Hierarchical Multimodal Attention-based Human Activity Recognition Algorithm
Gimme Signals: Discriminative signal encoding for multimodal activity recognition
Activity recognition using ST-GCN with 3D motion data
Can a simple approach identify complex nurse care activity?
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures
Autonomous Human Activity Classification from Ego-vision Camera and Accelerometer Data
EV-Action: Electromyography-Vision Multi-Modal Action Dataset
STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection
Adaptive Feature Processing for Robust Human Activity Recognition on a Novel Multi-Modal Dataset
Action Machine: Rethinking Action Recognition in Trimmed Videos
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Moments in Time Dataset: one million videos for event understanding
Interpretable 3D Human Action Analysis with Temporal Convolutional Networks
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Deep Multimodal Feature Analysis for Action Recognition in RGB+D Videos
Action recognition from depth maps using deep convolutional neural networks
Multimodal Multipart Learning for Action Recognition in Depth Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.