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Found 10 papers, 1 papers with code
Video-based Human Action Recognition using Deep Learning: A Review
Human action recognition is an important application domain in computer vision.
Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimationand 3D Object Detection
This paper presents SLS-Fusion, a new approach to fuse data from 4-beam LiDAR and a stereo camera via a neural network for depth estimation to achieve better dense depth maps and thereby improves 3D object detection performance.
Improving Vehicle Re-Identification using CNN Latent Spaces: Metrics Comparison and Track-to-track Extension
We compared T2TP with I2TP using the same CNN models.
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera
In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition.
Ranked #80 on
3D Human Pose Estimation
on Human3.6M
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data
We achieve promising results on real conditions of this dataset with the support of data augmentation and transfer learning techniques.
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks
In this paper we introduce a new skeleton-based representation for 3D action recognition in videos.
Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks
For learning and recognition tasks, we design and optimize new D-CNNs based on the idea of Inception Residual networks to predict actions from SPMFs.
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks
Automatic human action recognition is indispensable for almost artificial intelligent systems such as video surveillance, human-computer interfaces, video retrieval, etc.
Exploiting deep residual networks for human action recognition from skeletal data
In this paper, we investigate and apply deep ResNets for human action recognition using skeletal data provided by depth sensors.
Interactive multiclass segmentation using superpixel classification
This paper adresses the problem of interactive multiclass segmentation.
