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20232026
most citedVRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding

9 citations · 24 across the 13 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

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

InfiniBench: A Benchmark for Large Multi-Modal Models in Long-Form Movies and TV Shows

Kirolos Ataallah, Eslam Abdelrahman, Mahmoud Ahmed +4

Understanding long-form videos, such as movies and TV episodes ranging from tens of minutes to two hours, remains a significant challenge for multi-modal models. Existing benchmark…

cs.CV2024★ 9 cited

VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding

Xiang Li, Jian Ding, Mohamed Elhoseiny

We introduce a new benchmark designed to advance the development of general-purpose, large-scale vision-language models for remote sensing images. Although several vision-language…

cs.CV2024

iMotion-LLM: Instruction-Conditioned Trajectory Generation

Abdulwahab Felemban, Nussair Hroub, Jian Ding +4

We introduce iMotion-LLM, a large language model (LLM) integrated with trajectory prediction modules for interactive motion generation. Unlike conventional approaches, it generates…

cs.CV2024

Kestrel: 3D Multimodal LLM for Part-Aware Grounded Description

Mahmoud Ahmed, Junjie Fei, Jian Ding +2

In this paper, we introduce Part-Aware Point Grounded Description (PaPGD), a challenging task aimed at advancing 3D multimodal learning for fine-grained, part-aware segmentation gr…

cs.CV2024★ 8 cited

When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models

Xianzheng Ma, Brandon Smart, Yash Bhalgat +14

As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interact…

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…