activity
20242026
collaborators

8 papers

cs.LG2026

Permutation-Equivariant Flow Matching for Alignment-Free Neural Weight Generation

Arkadi Piven, Yam Eitan, Guy Bar-Shalom +5

A trained neural network can be represented by a parameter vector in high dimensions. Learning distributions over these vectors enables the generation of new models across various…

cs.CV2025

Learning Eigenstructures of Unstructured Data Manifolds

Roy Velich, Arkadi Piven, David Bensaïd +3

We introduce a novel framework that directly learns a spectral basis for shape and manifold analysis from unstructured data, eliminating the need for traditional operator selection…

cs.CV2025

Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising

Assaf Singer, Noam Rotstein, Amir Mann +2

Diffusion-based video generation can create realistic videos, yet existing image- and text-based conditioning fails to offer precise motion control. Prior methods for motion-condit…

cs.AI2025

SingLoRA: Low Rank Adaptation Using a Single Matrix

David Bensaïd, Noam Rotstein, Roy Velich +2

Low-Rank Adaptation (LoRA) has significantly advanced parameter-efficient fine-tuning of large pretrained models. LoRA augments the pre-trained weights of a model by adding the pro…

cs.CV2025

Neural Descriptors: Self-Supervised Learning of Robust Local Surface Descriptors Using Polynomial Patches

Gal Yona, Roy Velich, Ron Kimmel +1

Classical shape descriptors such as Heat Kernel Signature (HKS), Wave Kernel Signature (WKS), and Signature of Histograms of OrienTations (SHOT), while widely used in shape analysi…

cs.CV2025

CoordFlow: Coordinate Flow for Pixel-wise Neural Video Representation

Daniel Silver, Ron Kimmel

In the field of video compression, the pursuit for better quality at lower bit rates remains a long-lasting goal. Recent developments have demonstrated the potential of Implicit Ne…

cs.CV2024

Pathways on the Image Manifold: Image Editing via Video Generation

Noam Rotstein, Gal Yona, Daniel Silver +3

Recent advances in image editing, driven by image diffusion models, have shown remarkable progress. However, significant challenges remain, as these models often struggle to follow…

cs.CV2024

Paint by Inpaint: Learning to Add Image Objects by Removing Them First

Navve Wasserman, Noam Rotstein, Roy Ganz +1

Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual ins…