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20212026
most citedMiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

484 citations · 611 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.CV2024

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…

cs.CV2024

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"…

cs.CV2024★ 6 cited

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…

cs.CV2023★ 67 cited

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…

cs.CV2023★ 4 cited

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…

cs.CV2023

Video ChatCaptioner: Towards Enriched Spatiotemporal Descriptions

Jun Chen, Deyao Zhu, Kilichbek Haydarov +2

Video captioning aims to convey dynamic scenes from videos using natural language, facilitating the understanding of spatiotemporal information within our environment. Although the…

cs.CV2023★ 484 cited

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Deyao Zhu, Jun Chen, Xiaoqian Shen +2

The recent GPT-4 has demonstrated extraordinary multi-modal abilities, such as directly generating websites from handwritten text and identifying humorous elements within images. T…

cs.CV2023★ 40 cited

ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions

Deyao Zhu, Jun Chen, Kilichbek Haydarov +3

Asking insightful questions is crucial for acquiring knowledge and expanding our understanding of the world. However, the importance of questioning has been largely overlooked in A…

cs.CV2022★ 3 cited

Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation

Abduallah Mohamed, Deyao Zhu, Warren Vu +2

Best-of-N (BoN) Average Displacement Error (ADE)/ Final Displacement Error (FDE) is the most used metric for evaluating trajectory prediction models. Yet, the BoN does not quantify…

cs.CV2021★ 1 cited

RelTransformer: A Transformer-Based Long-Tail Visual Relationship Recognition

Jun Chen, Aniket Agarwal, Sherif Abdelkarim +2

The visual relationship recognition (VRR) task aims at understanding the pairwise visual relationships between interacting objects in an image. These relationships typically have a…