Multimodal Activity Recognition
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Benchmarks
EV-Action
Moments in Time Dataset
UTD-MHAD
LboroHAR
MMAct
UCSD-MIT Human Motion
UT-Kinect
Most implemented
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Moments in Time Dataset: one million videos for event understanding
Gimme Signals: Discriminative signal encoding for multimodal activity recognition
Papers
MuMu: Cooperative Multitask Learning-based Guided Multimodal Fusion
Multimodal sensors (visual, non-visual, and wearable) can provide complementary information to develop robust perception systems for recognizing activities accurately. However, it is challenging to extract robust multimo…
Activity RecognitionHuman Activity RecognitionMultimodal Activity RecognitionOPERAnet: A Multimodal Activity Recognition Dataset Acquired from Radio Frequency and Vision-based Sensors
This paper presents a comprehensive dataset intended to evaluate passive Human Activity Recognition (HAR) and localization techniques with measurements obtained from synchronized Radio-Frequency (RF) devices and vision-b…
Activity RecognitionHuman Activity RecognitionMultimodal Activity RecognitionFusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks
In this paper, we present Fusion-GCN, an approach for multimodal action recognition using Graph Convolutional Networks (GCNs). Action recognition methods based around GCNs recently yielded state-of-the-art performance fo…
Action RecognitionMultimodal Activity RecognitionSkeleton Based Action RecognitionDistilling Audio-Visual Knowledge by Compositional Contrastive Learning
Having access to multi-modal cues (e.g. vision and audio) empowers some cognitive tasks to be done faster compared to learning from a single modality. In this work, we propose to transfer knowledge across heterogeneous m…
Audio Taggingaudio-visual learningContrastive LearningKnowledge Distillation+3Multi-GAT: A Graphical Attention-based Hierarchical Multimodal Representation Learning Approach for Human Activity Recognition
Recognizing human activities is one of the crucial capabilities that a robot needs to have to be useful around people. Although modern robots are equipped with various types of sensors, human activity recognition (HAR) s…
Activity RecognitionHuman Activity RecognitionMixture-of-ExpertsMultimodal Activity Recognition+1Gimme Signals: Discriminative signal encoding for multimodal activity recognition
We present a simple, yet effective and flexible method for action recognition supporting multiple sensor modalities. Multivariate signal sequences are encoded in an image and are then classified using a recently proposed…
Action RecognitionActivity RecognitionMultimodal Activity RecognitionSkeleton Based Action Recognition