3D Action Recognition
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Benchmarks
Most implemented
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
TSM: Temporal Shift Module for Efficient Video Understanding
Unsupervised Learning of Object Keypoints for Perception and Control
Revisiting Skeleton-based Action Recognition
Papers
STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding
4D point cloud videos capture rich spatial and temporal dynamics of scenes which possess unique values in various 4D understanding tasks. However, most existing methods work in the spatiotemporal domain where the underly…
Representation Learning3D Action RecognitionSemantic SegmentationAlign then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception
Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are far scarcer than 3D ones, which hampers the scalability of self-supervised…
3D Action RecognitionSemantic SegmentationAction SegmentationTransfer LearningLearning Topology-Driven Multi-Subspace Fusion for Grassmannian Deep Network
Grassmannian manifold offers a powerful carrier for geometric representation learning by modelling high-dimensional data as low-dimensional subspaces. However, existing approaches predominantly rely on static single-subs…
Representation Learning3D Action RecognitionInformative Sample Selection Model for Skeleton-based Action Recognition with Limited Training Samples
Skeleton-based human action recognition aims to classify human skeletal sequences, which are spatiotemporal representations of actions, into predefined categories. To reduce the reliance on costly annotations of skeletal…
3D Action RecognitionActive LearningHuman Action Recognition from Point Clouds over Time
Recent research into human action recognition (HAR) has focused predominantly on skeletal action recognition and video-based methods. With the increasing availability of consumer-grade depth sensors and Lidar instruments…
Monocular Depth Estimation3D Action RecognitionPoint CloudsCHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Skeleton-based multi-entity action recognition is a challenging task aiming to identify interactive actions or group activities involving multiple diverse entities. Existing models for individuals often fall short in thi…
3D Action RecognitionAction RecognitionGroup Activity RecognitionHuman Interaction Recognition+1