3D Action Recognition

38 papers with code • 3 benchmarks • 14 datasets

Image: Rahmani et al

Libraries

Use these libraries to find 3D Action Recognition models and implementations
2 papers
4,315

Most implemented papers

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

adityac94/Grad_CAM_plus_plus 30 Oct 2017

Over the last decade, Convolutional Neural Network (CNN) models have been highly successful in solving complex vision problems.

TSM: Temporal Shift Module for Efficient Video Understanding

MIT-HAN-LAB/temporal-shift-module ICCV 2019

The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost.

Unsupervised Learning of Object Keypoints for Perception and Control

deepmind/deepmind-research NeurIPS 2019

In this work we aim to learn object representations that are useful for control and reinforcement learning (RL).

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

benedekrozemberczki/pytorch_geometric_temporal CVPR 2019

In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.

Revisiting Skeleton-based Action Recognition

open-mmlab/mmaction2 CVPR 2022

In this work, we propose PoseC3D, a new approach to skeleton-based action recognition, which relies on a 3D heatmap stack instead of a graph sequence as the base representation of human skeletons.

Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition

kenziyuliu/ms-g3d CVPR 2020

Spatial-temporal graphs have been widely used by skeleton-based action recognition algorithms to model human action dynamics.

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

shahroudy/NTURGB-D CVPR 2016

Recent approaches in depth-based human activity analysis achieved outstanding performance and proved the effectiveness of 3D representation for classification of action classes.

Reconstructing undersampled photoacoustic microscopy images using deep learning

axd465/PAM_Deep_Learning_Undersampling_Publication 30 May 2020

One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed.

Interpretable 3D Human Action Analysis with Temporal Convolutional Networks

TaeSoo-Kim/TCNActionRecognition 14 Apr 2017

In this work, we propose to use a new class of models known as Temporal Convolutional Neural Networks (TCN) for 3D human action recognition.

Investigation of Different Skeleton Features for CNN-based 3D Action Recognition

dzwallkilled/IEforAR 2 May 2017

The proposed method achieved state-of-the-art performance on NTU RGB+D dataset for 3D human action analysis.