49 citations · 128 across the 29 of their papers we have counts for
5 papers · 2 filters
PixFoundation 2.0: Do Video Multi-Modal LLMs Use Motion in Visual Grounding?
Mennatullah Siam
Multi-modal large language models (MLLMs) have shown impressive generalization across tasks using images and text modalities. While their extension to video has enabled tasks such…
Multiscale Video Transformers for Class Agnostic Segmentation in Autonomous Driving
Leila Cheshmi, Mennatullah Siam
Ensuring safety in autonomous driving is a complex challenge requiring handling unknown objects and unforeseen driving scenarios. We develop multiscale video transformers capable o…
The Power of One: A Single Example is All it Takes for Segmentation in VLMs
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal +1
Large-scale vision-language models (VLMs), trained on extensive datasets of image-text pairs, exhibit strong multimodal understanding capabilities by implicitly learning associatio…
A Vision Centric Remote Sensing Benchmark
Abduljaleel Adejumo, Faegheh Yeganli, Clifford Broni-bediako +3
Multimodal Large Language Models (MLLMs) have achieved remarkable success in vision-language tasks but their remote sensing (RS) counterpart are relatively under explored. Unlike n…
PixFoundation: Are We Heading in the Right Direction with Pixel-level Vision Foundation Models?
Mennatullah Siam
Multiple works have emerged to push the boundaries of multi-modal large language models (MLLMs) towards pixel-level understanding. The current trend is to train MLLMs with pixel-le…