32 citations · 100 across the 47 of their papers we have counts for
4 papers · 2 filters
Multi-View Foundation Models
Leo Segre, Or Hirschorn, Shai Avidan
Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature representation that is useful for various…
Talking Points: Describing and Localizing Pixels
Matan Rusanovsky, Shimon Malnick, Shai Avidan
Vision-language models have achieved remarkable success in cross-modal understanding. Yet, these models remain limited to object-level or region-level grounding, lacking the capabi…
TextureSAM: Towards a Texture Aware Foundation Model for Segmentation
Inbal Cohen, Boaz Meivar, Peihan Tu +2
Segment Anything Models (SAM) have achieved remarkable success in object segmentation tasks across diverse datasets. However, these models are predominantly trained on large-scale…
Frequency-Aware Gaussian Splatting Decomposition
Yishai Lavi, Leo Segre, Shai Avidan
3D Gaussian Splatting (3D-GS) enables efficient novel view synthesis, but treats all frequencies uniformly, making it difficult to separate coarse structure from fine detail. Recen…