168 citations · 342 across the 22 of their papers we have counts for
4 papers · 1 filter
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 (…
CLIPasso: Semantically-Aware Object Sketching
Yael Vinker, Ehsan Pajouheshgar, Jessica Y. Bo +5
Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings. Abstraction entails identifying the essential visual properties of an object or scen…
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…
SketchPatch: Sketch Stylization via Seamless Patch-level Synthesis
Noa Fish, Lilach Perry, Amit Bermano +1
The paradigm of image-to-image translation is leveraged for the benefit of sketch stylization via transfer of geometric textural details. Lacking the necessary volumes of data for…