704 citations · 750 across the 6 of their papers we have counts for
6 papers
Neural Alignment for Face De-pixelization
Maayan Shuvi, Noa Fish, Kfir Aberman +2
We present a simple method to reconstruct a high-resolution video from a face-video, where the identity of a person is obscured by pixelization. This concealment method is popular…
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…
Focus-and-Expand: Training Guidance Through Gradual Manipulation of Input Features
Moab Arar, Noa Fish, Dani Daniel +3
We present a simple and intuitive Focus-and-eXpand (\fax) method to guide the training process of a neural network towards a specific solution. Optimizing a neural network is a hig…
Image Morphing with Perceptual Constraints and STN Alignment
Noa Fish, Richard Zhang, Lilach Perry +3
In image morphing, a sequence of plausible frames are synthesized and composited together to form a smooth transformation between given instances. Intermediates must remain faithfu…
MeshCNN: A Network with an Edge
Rana Hanocka, Amir Hertz, Noa Fish +3
Polygonal meshes provide an efficient representation for 3D shapes. They explicitly capture both shape surface and topology, and leverage non-uniformity to represent large flat reg…
ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning
Rana Hanocka, Noa Fish, Zhenhua Wang +3
The process of aligning a pair of shapes is a fundamental operation in computer graphics. Traditional approaches rely heavily on matching corresponding points or features to guide…