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New era has unlocked exciting possibilities for extending Large Language Models (LLMs) to tackle 3D vision-language tasks. However, most existing 3D multimodal LLMs (MLLMs) rely on compressing holistic 3D scene information or segmenting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xiaoyan Wang , Zeju Li , Yifan Xu , Jiaxing Qi , Zhifei Yang , Ruifei Ma , Xiangde Liu , Chao Zhang

Recent advances in diffusion models have demonstrated exceptional capabilities in image and video generation, further improving the effectiveness of 4D synthesis. Existing 4D generation methods can generate high-quality 4D objects or scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Bohan Zeng , Ling Yang , Siyu Li , Jiaming Liu , Zixiang Zhang , Juanxi Tian , Kaixin Zhu , Yongzhen Guo , Fu-Yun Wang , Minkai Xu , Stefano Ermon , Wentao Zhang

Recent progress in pre-trained diffusion models and 3D generation have spurred interest in 4D content creation. However, achieving high-fidelity 4D generation with spatial-temporal consistency remains a challenge. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yifei Zeng , Yanqin Jiang , Siyu Zhu , Yuanxun Lu , Youtian Lin , Hao Zhu , Weiming Hu , Xun Cao , Yao Yao

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

Recent large multimodal models (LMMs) have become increasingly capable on image and video understanding, yet still struggle to sustain 4D continuous spatiotemporal dynamic reasoning. To study this capability gap, we formulate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Chaoyue Li , Yongxue Xu , Jie Feng , Jiayu Ding

Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-centric or rely on costly training for inter-object reasoning.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yaxu Xie , Abdalla Arafa , Alireza Javanmardi , Christen Millerdurai , Jia Cheng Hu , Shaoxiang Wang , Alain Pagani , Didier Stricker

Understanding a 3D scene immediately with its exploration is essential for embodied tasks, where an agent must construct and comprehend the 3D scene in an online and nearly real-time manner. In this study, we propose EmbodiedSplat, an…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Seungjun Lee , Zihan Wang , Yunsong Wang , Gim Hee Lee

Precisely perceiving the geometric and semantic properties of real-world 3D objects is crucial for the continued evolution of augmented reality and robotic applications. To this end, we present Foundation Model Embedded Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Xingxing Zuo , Pouya Samangouei , Yunwen Zhou , Yan Di , Mingyang Li

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

3D Gaussian Splatting (3DGS) has become horsepower in high-quality, real-time rendering for novel view synthesis of 3D scenes. However, existing methods focus primarily on geometric and appearance modeling, lacking deeper scene…

Graphics · Computer Science 2025-07-01 Minchao Jiang , Shunyu Jia , Jiaming Gu , Xiaoyuan Lu , Guangming Zhu , Anqi Dong , Liang Zhang

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

Training models to apply common-sense linguistic knowledge and visual concepts from 2D images to 3D scene understanding is a promising direction that researchers have only recently started to explore. However, it still remains understudied…

Computer Vision and Pattern Recognition · Computer Science 2023-06-12 Alexandros Delitzas , Maria Parelli , Nikolas Hars , Georgios Vlassis , Sotirios Anagnostidis , Gregor Bachmann , Thomas Hofmann

As 3D Gaussian Splatting (3DGS) emerges as a leading approach for novel view synthesis and scene reconstruction, its potential in digital asset creation has gained significant attention. An increasing number of asset libraries based on GS…

Human-Computer Interaction · Computer Science 2026-04-16 Haotian Mao , Hangyu Zhou , Zhuoxiong Xu , Siyue Wei , Yule Quan , Yan Zhang , Zixuan Guo , Nianchen Deng , Xubo Yang

Multimodal Large Language Models (MLLMs) have made significant progress in tasks such as image captioning and question answering. However, while these models can generate realistic captions, they often struggle with providing precise…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Chun-Peng Chang , Alain Pagani , Didier Stricker

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

Understanding the real world through point cloud video is a crucial aspect of robotics and autonomous driving systems. However, prevailing methods for 4D point cloud recognition have limitations due to sensor resolution, which leads to a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Zhichao Deng , Xiangtai Li , Xia Li , Yunhai Tong , Shen Zhao , Mengyuan Liu

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao

Recent developments in Multimodal Large Language Models (MLLMs) have significantly improved Vision-Language (VL) reasoning in 2D domains. However, extending these capabilities to 3D scene understanding remains a major challenge. Existing 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Haijier Chen , Bo Xu , Shoujian Zhang , Haoze Liu , Jiaxuan Lin , Jingrong Wang

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim