Search Results for author:
Found 17 papers, 4 papers with code
TOP-Nav: Legged Navigation Integrating Terrain, Obstacle and Proprioception Estimation
Within the path planner, we present and integrate a terrain estimator that enables the robot to select waypoints on terrains with higher traversability while effectively avoiding obstacles.
Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes
Specifically, Gaussian encoding and the grid-based strategy are applied to predict grasp heatmaps as guidance to aggregate local points into graspable regions and provide global semantic information.
Ranked #4 on
Robotic Grasping
on GraspNet-1Billion
DeGCN: Deformable Graph Convolutional Networks for Skeleton-Based Action Recognition
Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition.
Ranked #1 on
Skeleton Based Action Recognition
on NTU RGB+D 120
Category-Agnostic Pose Estimation for Point Clouds
The goal of object pose estimation is to visually determine the pose of a specific object in the RGB-D input.
MVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring
However, it is challenging to develop a single-lead-based ECG interpretation model for multiple diseases diagnosis due to the lack of some key disease information.
A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification
Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs).
ADMP: An Adversarial Double Masks Based Pruning Framework For Unsupervised Cross-Domain Compression
For example, the model is first pruned on the cloud and then transferred from cloud to end by UDA.
Bi-stream Pose Guided Region Ensemble Network for Fingertip Localization from Stereo Images
To mitigate these limitations and promote further research on hand pose estimation from stereo images, we propose a new large-scale binocular hand pose dataset called THU-Bi-Hand, offering a new perspective for fingertip localization.
SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds
The semantic segmentation network assigns semantic labels for each point in the point set.
Ranked #7 on
Hand Pose Estimation
on MSRA Hands
Two-Stream Binocular Network: Accurate Near Field Finger Detection Based On Binocular Images
Different from previous works, we propose a new framework, named Two-Stream Binocular Network (TSBnet) to detect fingertips from binocular images directly.
Interactive Hand Pose Estimation: Boosting accuracy in localizing extended finger joints
In the reality of HMI, joints in fingers stretching out, especially corresponding fingertips, are much more important than other joints.
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
Ranked #5 on
Hand Pose Estimation
on HANDS 2017
Pose Guided Structured Region Ensemble Network for Cascaded Hand Pose Estimation
The proposed method extracts regions from the feature maps of convolutional neural network under the guide of an initially estimated pose, generating more optimal and representative features for hand pose estimation.
Ranked #8 on
Hand Pose Estimation
on HANDS 2017
Motion Feature Augmented Recurrent Neural Network for Skeleton-based Dynamic Hand Gesture Recognition
Dynamic hand gesture recognition has attracted increasing interests because of its importance for human computer interaction.
Ranked #6 on
Hand Gesture Recognition
on DHG-28
Towards Good Practices for Deep 3D Hand Pose Estimation
3D hand pose estimation from single depth image is an important and challenging problem for human-computer interaction.
Ranked #4 on
Pose Estimation
on ITOP top-view
Region Ensemble Network: Improving Convolutional Network for Hand Pose Estimation
Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction.
Ranked #11 on
Hand Pose Estimation
on MSRA Hands
Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information
Accurate detection of fingertips in depth image is critical for human-computer interaction.
