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Comprehending text-rich visual content is paramount for the practical application of Multimodal Large Language Models (MLLMs), since text-rich scenarios are ubiquitous in the real world, which are characterized by the presence of extensive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Bohao Li , Yuying Ge , Yi Chen , Yixiao Ge , Ruimao Zhang , Ying Shan

Recent advancements in object-centric text-to-3D generation have shown impressive results. However, generating complex 3D scenes remains an open challenge due to the intricate relations between objects. Moreover, existing methods are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yu-Hsiang Huang , Wei Wang , Sheng-Yu Huang , Yu-Chiang Frank Wang

Three-Dimensional (3D) dense captioning is an emerging vision-language bridging task that aims to generate multiple detailed and accurate descriptions for 3D scenes. It presents significant potential and challenges due to its closer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Ting Yu , Xiaojun Lin , Shuhui Wang , Weiguo Sheng , Qingming Huang , Jun Yu

While multi-modality large language models excel in object-centric or indoor scenarios, scaling them to 3D city-scale environments remains a formidable challenge. To bridge this gap, we propose 3DCity-LLM, a unified framework designed for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Yiping Chen , Jinpeng Li , Wenyu Ke , Yang Luo , Jie Ouyang , Zhongjie He , Li Liu , Hongchao Fan , Hao Wu

Scene synthesis and editing has emerged as a promising direction in computer graphics. Current trained approaches for 3D indoor scene generation either oversimplify object semantics through one-hot class encodings (e.g., 'chair' or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Martin JJ. Bucher , Iro Armeni

As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interacting with physical spaces. This survey provides a…

Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Yining Hong , Haoyu Zhen , Peihao Chen , Shuhong Zheng , Yilun Du , Zhenfang Chen , Chuang Gan

Video Multimodal Large Language Models (MLLMs) have shown remarkable capability of understanding the video semantics on various downstream tasks. Despite the advancements, there is still a lack of systematic research on visual context…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Yifan Du , Yuqi Huo , Kun Zhou , Zijia Zhao , Haoyu Lu , Han Huang , Wayne Xin Zhao , Bingning Wang , Weipeng Chen , Ji-Rong Wen

3D visual grounding aims to localize the unique target described by natural languages in 3D scenes. The significant gap between 3D and language modalities makes it a notable challenge to distinguish multiple similar objects through the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Feng Xiao , Hongbin Xu , Guocan Zhao , Wenxiong Kang

A comprehensive semantic understanding of a scene is important for many applications - but in what space should diverse semantic information (e.g., objects, scene categories, material types, texture, etc.) be grounded and what should be its…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Iro Armeni , Zhi-Yang He , JunYoung Gwak , Amir R. Zamir , Martin Fischer , Jitendra Malik , Silvio Savarese

Designing high-quality indoor 3D scenes is important in many practical applications, such as room planning or game development. Conventionally, this has been a time-consuming process which requires both artistic skill and familiarity with…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Başak Melis Öcal , Maxim Tatarchenko , Sezer Karaoglu , Theo Gevers

Multi-modal 3D scene understanding has gained considerable attention due to its wide applications in many areas, such as autonomous driving and human-computer interaction. Compared to conventional single-modal 3D understanding, introducing…

Computer Vision and Pattern Recognition · Computer Science 2023-10-25 Yinjie Lei , Zixuan Wang , Feng Chen , Guoqing Wang , Peng Wang , Yang Yang

In recent years, 2D Vision-Language Models (VLMs) have made significant strides in image-text understanding tasks. However, their performance in 3D spatial comprehension, which is critical for embodied intelligence, remains limited. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhangyang Qi , Zhixiong Zhang , Ye Fang , Jiaqi Wang , Hengshuang Zhao

Multi-view understanding, the ability to reconcile visual information across diverse viewpoints for effective navigation, manipulation, and 3D scene comprehension, is a fundamental challenge in Multi-Modal Large Language Models (MLLMs) to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chun-Hsiao Yeh , Chenyu Wang , Shengbang Tong , Ta-Ying Cheng , Ruoyu Wang , Tianzhe Chu , Yuexiang Zhai , Yubei Chen , Shenghua Gao , Yi Ma

Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined spatial relationships, limiting their capacity for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jun Luo , Jiaxiang Tang , Ruijie Lu , Gang Zeng

Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. However, existing schemes for 3D scene editing still exhibit certain shortcomings,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Shuangkang Fang , Yufeng Wang , Yi-Hsuan Tsai , Yi Yang , Wenrui Ding , Shuchang Zhou , Ming-Hsuan Yang

Open-world instance-level scene understanding aims to locate and recognize unseen object categories that are not present in the annotated dataset. This task is challenging because the model needs to both localize novel 3D objects and infer…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Runyu Ding , Jihan Yang , Chuhui Xue , Wenqing Zhang , Song Bai , Xiaojuan Qi

We address the new problem of language-guided semantic style transfer of 3D indoor scenes. The input is a 3D indoor scene mesh and several phrases that describe the target scene. Firstly, 3D vertex coordinates are mapped to RGB residues by…

Computer Vision and Pattern Recognition · Computer Science 2022-08-17 Bu Jin , Beiwen Tian , Hao Zhao , Guyue Zhou

Understanding functionalities in 3D scenes involves interpreting natural language descriptions to locate functional interactive objects, such as handles and buttons, in a 3D environment. Functionality understanding is highly challenging, as…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Jaime Corsetti , Francesco Giuliari , Alice Fasoli , Davide Boscaini , Fabio Poiesi

This paper addresses the high demand in advanced intelligent robot navigation for a more holistic understanding of spatial environments, by introducing a novel system that harnesses the capabilities of Large Language Models (LLMs) to…

Robotics · Computer Science 2025-03-20 Yao Cheng , Zhe Han , Fengyang Jiang , Huaizhen Wang , Fengyu Zhou , Qingshan Yin , Lei Wei
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