3D Geometry Prediction
5 papers with code • 2 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in 3D Geometry Prediction
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Molecule3D
DrivAerNet
Most implemented papers
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs
Here, we propose to predict the ground-state 3D geometries from molecular graphs using machine learning methods.
Hierarchical Surface Prediction for 3D Object Reconstruction
A major limitation of such approaches is that they only predict a coarse resolution voxel grid, which does not capture the surface of the objects well.
Learning 6-DOF Grasping Interaction via Deep Geometry-aware 3D Representations
koryako/selfcarRaspberryPi
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Our contributions are fourfold: (1) To best of our knowledge, we are presenting for the first time a method to learn a 6-DOF grasping net from RGBD input; (2) We build a grasping dataset from demonstrations in virtual reality with rich sensory and interaction annotations.
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
dptech-corp/Uni-Mol
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ChemRxiv 2022
Uni-Mol is composed of two models with the same SE(3)-equivariant transformer architecture: a molecular pretraining model trained by 209M molecular conformations; a pocket pretraining model trained by 3M candidate protein pocket data.
Point Cloud Diffusion Models for Automatic Implant Generation
Advances in 3D printing of biocompatible materials make patient-specific implants increasingly popular.
