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cs.CV2026

PREGEN: Uncovering Latent Thoughts in Composed Video Retrieval

Gabriele Serussi, David Vainshtein, Jonathan Kouchly +2

Composed Video Retrieval (CoVR) aims to retrieve a video based on a query video and a modifying text. Current CoVR methods fail to fully exploit modern Vision-Language Models (VLMs…

cs.CV2025

Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge

Nimrod Berman, Omkar Joglekar, Eitan Kosman +2

Recent advances in generative modeling have positioned diffusion models as state-of-the-art tools for sampling from complex data distributions. While these models have shown remark…

cs.CV2025

Robot Instance Segmentation with Few Annotations for Grasping

Moshe Kimhi, David Vainshtein, Chaim Baskin +1

The ability of robots to manipulate objects relies heavily on their aptitude for visual perception. In domains characterized by cluttered scenes and high object variability, most m…

cs.CV2024

Radar Spectra-Language Model for Automotive Scene Parsing

Mariia Pushkareva, Yuri Feldman, Csaba Domokos +2

Radar sensors are low cost, long-range, and weather-resilient. Therefore, they are widely used for driver assistance functions, and are expected to be crucial for the success of au…

cs.CV2024

ISCUTE: Instance Segmentation of Cables Using Text Embedding

Shir Kozlovsky, Omkar Joglekar, Dotan Di Castro

In the field of robotics and automation, conventional object recognition and instance segmentation methods face a formidable challenge when it comes to perceiving Deformable Linear…