472 citations · 907 across the 31 of their papers we have counts for
6 papers · 1 filter
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…
MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement
Rinon Gal, Amit Bermano, Hao Zhang +1
We present MRGAN, a multi-rooted adversarial network which generates part-disentangled 3D point-cloud shapes without part-based shape supervision. The network fuses multiple branch…
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…
Face Identity Disentanglement via Latent Space Mapping
Yotam Nitzan, Amit Bermano, Yangyan Li +1
Learning disentangled representations of data is a fundamental problem in artificial intelligence. Specifically, disentangled latent representations allow generative models to cont…
Structural-analogy from a Single Image Pair
Sagie Benaim, Ron Mokady, Amit Bermano +2
The task of unsupervised image-to-image translation has seen substantial advancements in recent years through the use of deep neural networks. Typically, the proposed solutions lea…
Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation
Moab Arar, Yiftach Ginger, Dov Danon +3
Many applications, such as autonomous driving, heavily rely on multi-modal data where spatial alignment between the modalities is required. Most multi-modal registration methods st…