9 citations · 24 across the 13 of their papers we have counts for
11 papers · 1 filter
Esports World Model Dataset
Weiyu Ma, Zeyuan Gong, Xuhui Liu +5
Interactive world models must capture how multiple participants jointly change a shared environment while observing different parts of it. Competitive games make this challenge con…
Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning
Xuyang Wang, Zhenyu Li, Jian Ding +4
Reconstructing articulated objects from sparse images requires recovering complete geometry, movable parts, and motion parameters. Recent methods typically separate geometry recons…
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"…
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…
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…
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…
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…
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…
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…
Uni3DL: Unified Model for 3D and Language Understanding
Xiang Li, Jian Ding, Zhaoyang Chen +1
In this work, we present Uni3DL, a unified model for 3D and Language understanding. Distinct from existing unified vision-language models in 3D which are limited in task variety an…
Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer
Yaoting Wang, Weisong Liu, Guangyao Li +3
Never having seen an object and heard its sound simultaneously, can the model still accurately localize its visual position from the input audio? In this work, we concentrate on th…