Search Results for author:
Found 3 papers, 2 papers with code
PALO: A Polyglot Large Multimodal Model for 5B People
PALO offers visual reasoning capabilities in 10 major languages, including English, Chinese, Hindi, Spanish, French, Arabic, Bengali, Russian, Urdu, and Japanese, that span a total of ~5B people (65% of the world population).
GLaMM: Pixel Grounding Large Multimodal Model
In this work, we present Grounding LMM (GLaMM), the first model that can generate natural language responses seamlessly intertwined with corresponding object segmentation masks.
Portmanteau Vocabularies for Multi-Cue Image Representation
We describe a novel technique for feature combination in the bag-of-words model of image classification.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
