1 citations · 1 across the 4 of their papers we have counts for
4 papers
Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects
Amir Barda, Matheus Gadelha, Vladimir G. Kim +3
We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in approximately 3 seconds, without the need for running an SDS type of optim…
MagicClay: Sculpting Meshes With Generative Neural Fields
Amir Barda, Vladimir G. Kim, Noam Aigerman +2
The recent developments in neural fields have brought phenomenal capabilities to the field of shape generation, but they lack crucial properties, such as incremental control - a fu…
ROAR: Robust Adaptive Reconstruction of Shapes Using Planar Projections
Amir Barda, Yotam Erel, Yoni Kasten +1
The majority of existing large 3D shape datasets contain meshes that lend themselves extremely well to visual applications such as rendering, yet tend to be topologically invalid (…
MeshCNN Fundamentals: Geometric Learning through a Reconstructable Representation
Amir Barda, Yotam Erel, Amit H. Bermano
Mesh-based learning is one of the popular approaches nowadays to learn shapes. The most established backbone in this field is MeshCNN. In this paper, we propose infusing MeshCNN wi…