25 citations · 37 across the 8 of their papers we have counts for
5 papers · 1 filter
Propose and Attend: Training-free MLLM Grounding Confidence via Multi-Token Localized Attention
Daniel Shalam, Emanuel Ben Baruch, Avi Ben Cohen +1
Multimodal large language models can emit localized predictions, bounding boxes for objects and temporal windows for video and audio events, but they hallucinate these regions prol…
Class-Aware Fully-Convolutional Gaussian and Poisson Denoising
Tal Remez, Or Litany, Raja Giryes +1
We propose a fully-convolutional neural-network architecture for image denoising which is simple yet powerful. Its structure allows to exploit the gradual nature of the denoising p…
Learning to Segment via Cut-and-Paste
Tal Remez, Jonathan Huang, Matthew Brown
This paper presents a weakly-supervised approach to object instance segmentation. Starting with known or predicted object bounding boxes, we learn object masks by playing a game of…
Efficient Deformable Shape Correspondence via Kernel Matching
Zorah Lähner, Matthias Vestner, Amit Boyarski +8
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-…
Deep Class Aware Denoising
Tal Remez, Or Litany, Raja Giryes +1
The increasing demand for high image quality in mobile devices brings forth the need for better computational enhancement techniques, and image denoising in particular. At the same…