Search Results for author:
Found 4 papers, 2 papers with code
Distribution Consistent Neural Architecture Search
We first theoretically investigate how the weight coupling problem affects the network searching performance from a parameter distribution perspective, and then propose a novel supernet training strategy with a Distribution Consistent Constraint that can provide a good measurement for the extent to which two architectures can share weights.
Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks
The key to our approach is a novel progressive shaping framework that alternates between mesh deformation and topology modification.
Ranked #3 on
3D Shape Reconstruction
on Pix3D
A Skeleton-bridged Deep Learning Approach for Generating Meshesof Complex Topologies from Single RGB Image
To this end, we propose in this paper a skeleton-bridged, stage-wise learning approach to address the challenge.
A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images
To this end, we propose in this paper a skeleton-bridged, stage-wise learning approach to address the challenge.
