4 citations · 12 across the 12 of their papers we have counts for
13 papers
FM-ChangeNet: Learning Change through Pathwise Feature Transport
Roie Kazoom, George Leifman, Genady Beryozkin
We present FM-ChangeNet, a pathwise-supervised framework for change detection that reformulates bi-temporal reasoning as continuous transport in feature space rather than static en…
RS-OVC: Open-Vocabulary Counting for Remote-Sensing Data
Tamir Shor, George Leifman, Genady Beryozkin
Object-Counting for remote-sensing (RS) imagery is attracting increasing research interest due to its crucial role in a wide and diverse set of applications. While several promisin…
RSRCC: A Remote Sensing Regional Change Comprehension Benchmark Constructed via Retrieval-Augmented Best-of-N Ranking
Roie Kazoom, Yotam Gigi, George Leifman +2
Traditional change detection identifies where changes occur, but does not explain what changed in natural language. Existing remote sensing change captioning datasets typically des…
GroundSet: A Cadastral-Grounded Dataset for Spatial Understanding with Vector Data
Roger Ferrod, Maël Lecene, Krishna Sapkota +4
Precise spatial understanding in Earth Observation is essential for translating raw aerial imagery into actionable insights for critical applications like urban planning, environme…
On-the-Fly OVD Adaptation with FLAME: Few-shot Localization via Active Marginal-Samples Exploration
Yehonathan Refael, Amit Aides, Aviad Barzilai +5
Open-vocabulary object detection (OVD) models offer remarkable flexibility by detecting objects from arbitrary text queries. However, their zero-shot performance in specialized dom…
Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning
Aaron Bell, Amit Aides, Amr Helmy +57
Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…
A Recipe for Improving Remote Sensing VLM Zero Shot Generalization
Aviad Barzilai, Yotam Gigi, Amr Helmy +6
Foundation models have had a significant impact across various AI applications, enabling use cases that were previously impossible. Contrastive Visual Language Models (VLMs), in pa…
Anchored Diffusion for Video Face Reenactment
Idan Kligvasser, Regev Cohen, George Leifman +2
Video generation has drawn significant interest recently, pushing the development of large-scale models capable of producing realistic videos with coherent motion. Due to memory co…
Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models
Omer Belhasin, Idan Kligvasser, George Leifman +7
Analyzing the cardiovascular system condition via Electrocardiography (ECG) is a common and highly effective approach, and it has been practiced and perfected over many decades. EC…
Semi-supervised Quality Evaluation of Colonoscopy Procedures
Idan Kligvasser, George Leifman, Roman Goldenberg +2
Colonoscopy is the standard of care technique for detecting and removing polyps for the prevention of colorectal cancer. Nevertheless, gastroenterologists (GI) routinely miss appro…
Colonoscopy Coverage Revisited: Identifying Scanning Gaps in Real-Time
G. Leifman, I. Kligvasser, R. Goldenberg +2
Colonoscopy is the most widely used medical technique for preventing Colorectal Cancer, by detecting and removing polyps before they become malignant. Recent studies show that arou…
Weakly-supervised Representation Learning for Video Alignment and Analysis
Guy Bar-Shalom, George Leifman, Michael Elad +1
Many tasks in video analysis and understanding boil down to the need for frame-based feature learning, aiming to encapsulate the relevant visual content so as to enable simpler and…
Learning Gaze Transitions from Depth to Improve Video Saliency Estimation
G. Leifman, D. Rudoy, T. Swedish +2
In this paper we introduce a novel Depth-Aware Video Saliency approach to predict human focus of attention when viewing RGBD videos on regular 2D screens. We train a generative con…