67 citations · 122 across the 7 of their papers we have counts for
7 papers
How Well Can Vision Language Models See Image Details?
Chenhui Gou, Abdulwahab Felemban, Faizan Farooq Khan +4
Large Language Model-based Vision-Language Models (LLM-based VLMs) have demonstrated impressive results in various vision-language understanding tasks. However, how well these VLMs…
Goldfish: Vision-Language Understanding of Arbitrarily Long Videos
Kirolos Ataallah, Xiaoqian Shen, Eslam Abdelrahman +6
Most current LLM-based models for video understanding can process videos within minutes. However, they struggle with lengthy videos due to challenges such as "noise and redundancy"…
MiniGPT-Med: Large Language Model as a General Interface for Radiology Diagnosis
Asma Alkhaldi, Raneem Alnajim, Layan Alabdullatef +5
Recent advancements in artificial intelligence (AI) have precipitated significant breakthroughs in healthcare, particularly in refining diagnostic procedures. However, previous stu…
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
Kirolos Ataallah, Xiaoqian Shen, Eslam Abdelrahman +4
This paper introduces MiniGPT4-Video, a multimodal Large Language Model (LLM) designed specifically for video understanding. The model is capable of processing both temporal visual…
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Jun Chen, Deyao Zhu, Xiaoqian Shen +7
Large language models have shown their remarkable capabilities as a general interface for various language-related applications. Motivated by this, we target to build a unified int…
Exploring Open-Vocabulary Semantic Segmentation without Human Labels
Jun Chen, Deyao Zhu, Guocheng Qian +6
Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level. However, existing approaches oft…