6 citations · 18 across the 14 of their papers we have counts for
15 papers · 1 filter
Retrieval-Augmented Gaussian Avatars: Improving Expression Generalization
Matan Levy, Gavriel Habib, Issar Tzachor +5
Template-free animatable head avatars can achieve high visual fidelity by learning expression-dependent facial deformation directly from a subject's capture, avoiding parametric fa…
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…
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…
CarGait: Cross-Attention based Re-ranking for Gait recognition
Gavriel Habib, Noa Barzilay, Or Shimshi +2
Gait recognition is a computer vision task that identifies individuals based on their walking patterns. Gait recognition performance is commonly evaluated by ranking a gallery of c…
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…
Active Learning via Classifier Impact and Greedy Selection for Interactive Image Retrieval
Leah Bar, Boaz Lerner, Nir Darshan +1
Active Learning (AL) is a user-interactive approach aimed at reducing annotation costs by selecting the most crucial examples to label. Although AL has been extensively studied for…
EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition
Issar Tzachor, Boaz Lerner, Matan Levy +8
The task of Visual Place Recognition (VPR) is to predict the location of a query image from a database of geo-tagged images. Recent studies in VPR have highlighted the significant…
Where's Waldo: Diffusion Features for Personalized Segmentation and Retrieval
Dvir Samuel, Rami Ben-Ari, Matan Levy +2
Personalized retrieval and segmentation aim to locate specific instances within a dataset based on an input image and a short description of the reference instance. While supervise…
Advancing Image Retrieval with Few-Shot Learning and Relevance Feedback
Boaz Lerner, Nir Darshan, Rami Ben-Ari
With such a massive growth in the number of images stored, efficient search in a database has become a crucial endeavor managed by image retrieval systems. Image Retrieval with Rel…
Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models
Dvir Samuel, Barak Meiri, Haggai Maron +5
Diffusion inversion is the problem of taking an image and a text prompt that describes it and finding a noise latent that would generate the exact same image. Most current determin…
Watch Where You Head: A View-biased Domain Gap in Gait Recognition and Unsupervised Adaptation
Gavriel Habib, Noa Barzilay, Or Shimshi +2
Gait Recognition is a computer vision task aiming to identify people by their walking patterns. Although existing methods often show high performance on specific datasets, they lac…
Norm-guided latent space exploration for text-to-image generation
Dvir Samuel, Rami Ben-Ari, Nir Darshan +2
Text-to-image diffusion models show great potential in synthesizing a large variety of concepts in new compositions and scenarios. However, the latent space of initial seeds is sti…
Chatting Makes Perfect: Chat-based Image Retrieval
Matan Levy, Rami Ben-Ari, Nir Darshan +1
Chats emerge as an effective user-friendly approach for information retrieval, and are successfully employed in many domains, such as customer service, healthcare, and finance. How…
Generating images of rare concepts using pre-trained diffusion models
Dvir Samuel, Rami Ben-Ari, Simon Raviv +2
Text-to-image diffusion models can synthesize high-quality images, but they have various limitations. Here we highlight a common failure mode of these models, namely, generating un…
Data Roaming and Quality Assessment for Composed Image Retrieval
Matan Levy, Rami Ben-Ari, Nir Darshan +1
The task of Composed Image Retrieval (CoIR) involves queries that combine image and text modalities, allowing users to express their intent more effectively. However, current CoIR…