8 citations · 9 across the 8 of their papers we have counts for
9 papers
TrajLoc: Trajectory-Attention Localization for Multi-Object Motion Control
Omer Sela, Inbar Huberman-Spiegelglas, Michael Rotman +2
Controlling the motion of multiple objects in image-to-video (I2V) generation requires preserving object identities while enforcing adherence to distinct target trajectories. This…
MineTheGap: Automatic Mining of Biases in Text-to-Image Models
Noa Cohen, Nurit Spingarn-Eliezer, Inbar Huberman-Spiegelglas +1
Text-to-Image (TTI) models generate images based on text prompts, which often leave certain aspects of the desired image ambiguous. When faced with these ambiguities, TTI models ha…
Splatent: Splatting Diffusion Latents for Novel View Synthesis
Or Hirschorn, Omer Sela, Inbar Huberman-Spiegelglas +6
Radiance field representations have recently been explored in the latent space of VAEs that are commonly used by diffusion models. This direction offers efficient rendering and sea…
FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models
Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas +1
Editing real images using a pre-trained text-to-image (T2I) diffusion/flow model often involves inverting the image into its corresponding noise map. However, inversion by itself i…
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices
Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner +2
Text-to-image (T2I) diffusion models achieve state-of-the-art results in image synthesis and editing. However, leveraging such pretrained models for video editing is considered a m…
An Edit Friendly DDPM Noise Space: Inversion and Manipulations
Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli
Denoising diffusion probabilistic models (DDPMs) employ a sequence of white Gaussian noise samples to generate an image. In analogy with GANs, those noise maps could be considered…
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models
René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff +3
Denoising Diffusion Models (DDMs) have emerged as a strong competitor to Generative Adversarial Networks (GANs). However, despite their widespread use in image synthesis and editin…
Single Image Object Counting and Localizing using Active-Learning
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 rec…
Unpaired Learning for High Dynamic Range Image Tone Mapping
Yael Vinker, Inbar Huberman-Spiegelglas, Raanan Fattal
High dynamic range (HDR) photography is becoming increasingly popular and available by DSLR and mobile-phone cameras. While deep neural networks (DNN) have greatly impacted other d…