8 citations · 15 across the 4 of their papers we have counts for
6 papers
FOR: Finetuning for Object Level Open Vocabulary Image Retrieval
Hila Levi, Guy Heller, Dan Levi
As working with large datasets becomes standard, the task of accurately retrieving images containing objects of interest by an open set textual query gains practical importance. Th…
Object-Centric Open-Vocabulary Image-Retrieval with Aggregated Features
Hila Levi, Guy Heller, Dan Levi +1
The task of open-vocabulary object-centric image retrieval involves the retrieval of images containing a specified object of interest, delineated by an open-set text query. As work…
Detector-Free Weakly Supervised Grounding by Separation
Assaf Arbelle, Sivan Doveh, Amit Alfassy +14
Nowadays, there is an abundance of data involving images and surrounding free-form text weakly corresponding to those images. Weakly Supervised phrase-Grounding (WSG) deals with th…
Multi-Task Learning by a Top-Down Control Network
Hila Levi, Shimon Ullman
As the range of tasks performed by a general vision system expands, executing multiple tasks accurately and efficiently in a single network has become an important and still open p…
Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects
Hila Levi, Shimon Ullman
An image is not just a collection of objects, but rather a graph where each object is related to other objects through spatial and semantic relations. Using relational reasoning mo…
Deep Multi-Spectral Registration Using Invariant Descriptor Learning
Nati Ofir, Shai Silberstein, Hila Levi +3
In this paper, we introduce a novel deep-learning method to align cross-spectral images. Our approach relies on a learned descriptor which is invariant to different spectra. Multi-…