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Matan Levy

PhD Student at The Hebrew University of Jerusalem

13 papers hereh-index 7185 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author7

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • cs.GR1
affiliations
  • PhD Student at The Hebrew University of Jerusalem
Homepage
same name
  • Matan Levy — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedChatting Makes Perfect: Chat-based Image Retrieval

6 citations · 12 across the 13 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

Story2Board: A Training-Free Approach for Expressive Storyboard Generation

David Dinkevich, Matan Levy, Omri Avrahami +2

We present Story2Board, a training-free framework for expressive storyboard generation from natural language. Existing methods narrowly focus on subject identity, overlooking key a…

cs.CV2025

OmnimatteZero: Fast Training-free Omnimatte with Pre-trained Video Diffusion Models

Dvir Samuel, Matan Levy, Nir Darshan +2

In Omnimatte, one aims to decompose a given video into semantically meaningful layers, including the background and individual objects along with their associated effects, such as…

cs.CV2025

Find your Needle: Small Object Image Retrieval via Multi-Object Attention Optimization

Michael Green, Matan Levy, Issar Tzachor +3

We address the challenge of Small Object Image Retrieval (SoIR), where the goal is to retrieve images containing a specific small object, in a cluttered scene. The key challenge in…

cs.CV2025

Task-Specific Adaptation with Restricted Model Access

Matan Levy, Rami Ben-Ari, Dvir Samuel +2

The emergence of foundational models has greatly improved performance across various downstream tasks, with fine-tuning often yielding even better results. However, existing fine-t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.