3D Object Super-Resolution
2 papers with code • 0 benchmarks • 1 datasets
3D object super-resolution is the task of up-sampling 3D objects.
( Image credit: Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation )
Benchmarks
These leaderboards are used to track progress in 3D Object Super-Resolution
You can find evaluation results in the subtasks. You can also
submitting
evaluation metrics for this task.
Most implemented papers
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
We consider the problem of scaling deep generative shape models to high-resolution.
Learning Descriptor Networks for 3D Shape Synthesis and Analysis
This paper proposes a 3D shape descriptor network, which is a deep convolutional energy-based model, for modeling volumetric shape patterns.