Search Results for author: Inbar Huberman-Spiegelglas

Found 3 papers, 0 papers with code

Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models

no code implementations20 Mar 2023 René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, Tomer Michaeli

Recently, a semantic latent space for DDMs, coined `$h$-space', was shown to facilitate semantic image editing in a way reminiscent of GANs.

Denoising Image Generation

Single Image Object Counting and Localizing using Active-Learning

no code implementations16 Nov 2021 Inbar Huberman-Spiegelglas, Raanan Fattal

The need to count and localize repeating objects in an image arises in different scenarios, such as biological microscopy studies, production lines inspection, and surveillance recordings analysis.

Active Learning Object Counting +2

Unpaired Learning for High Dynamic Range Image Tone Mapping

no code implementations ICCV 2021 Yael Vinker, Inbar Huberman-Spiegelglas, Raanan Fattal

In this paper we describe a new tone-mapping approach guided by the distinct goal of producing low dynamic range (LDR) renditions that best reproduce the visual characteristics of native LDR images.

Image Manipulation Tone Mapping

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