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Found 3 papers, 2 papers with code
SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction
We also develop an edge-based atom-pair feature aggregation method to represent complex interactions and a graph pooling-based method to predict the binding affinity of the complex.
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.
HandAugment: A Simple Data Augmentation Method for Depth-Based 3D Hand Pose Estimation
Our method has two main parts: First, We propose a scheme of two-stage neural networks.
Ranked #2 on
Hand Pose Estimation
on HANDS 2019
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