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Recent 4D dynamic scene editing methods require editing thousands of 2D images used for dynamic scene synthesis and updating the entire scene with additional training loops, resulting in several hours of processing to edit a single dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Joohyun Kwon , Hanbyel Cho , Junmo Kim

The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding applications. However, it is a challenging task to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yuzhou Ji , He Zhu , Junshu Tang , Wuyi Liu , Zhizhong Zhang , Xin Tan , Yuan Xie

Simultaneous Localization and Mapping (SLAM) is one of the most important environment-perception and navigation algorithms for computer vision, robotics, and autonomous cars/drones. Hence, high quality and fast mapping becomes a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Runfa Blark Li , Mahdi Shaghaghi , Keito Suzuki , Xinshuang Liu , Varun Moparthi , Bang Du , Walker Curtis , Martin Renschler , Ki Myung Brian Lee , Nikolay Atanasov , Truong Nguyen

To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recently, a field called dynamic scene video has emerged, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 In-Hwan Jin , Haesoo Choo , Seong-Hun Jeong , Heemoon Park , Junghwan Kim , Oh-joon Kwon , Kyeongbo Kong

Recent 4D reconstruction methods have yielded impressive results but rely on sharp videos as supervision. However, motion blur often occurs in videos due to camera shake and object movement, while existing methods render blurry results when…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Renlong Wu , Zhilu Zhang , Mingyang Chen , Zifei Yan , Wangmeng Zuo

Open-vocabulary 3D scene understanding is crucial for robotics applications, such as natural language-driven manipulation, human-robot interaction, and autonomous navigation. Existing methods for querying 3D Gaussian Splatting often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Hairong Yin , Huangying Zhan , Yi Xu , Raymond A. Yeh

Combining 3D Gaussian splatting with Simultaneous Localization and Mapping (SLAM) has gained popularity as it enables continuous 3D environment reconstruction during motion. However, existing methods struggle in dynamic environments,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangfan Zhao , Hanwei Zhang , Ke Huang , Qiufeng Wang , Zhenzhou Shao , Dengyu Wu

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

Modeling and understanding the 3D world is crucial for various applications, from augmented reality to robotic navigation. Recent advancements based on 3D Gaussian Splatting have integrated semantic information from multi-view images into…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Xingrui Wang , Cuiling Lan , Hanxin Zhu , Zhibo Chen , Yan Lu

The latest emerged 4D Panoptic Scene Graph (4D-PSG) provides an advanced-ever representation for comprehensively modeling the dynamic 4D visual real world. Unfortunately, current pioneering 4D-PSG research can primarily suffer from data…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Shengqiong Wu , Hao Fei , Jingkang Yang , Xiangtai Li , Juncheng Li , Hanwang Zhang , Tat-seng Chua

We have introduced SegSplat, a novel framework designed to bridge the gap between rapid, feed-forward 3D reconstruction and rich, open-vocabulary semantic understanding. By constructing a compact semantic memory bank from multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Peter Siegel , Federico Tombari , Marc Pollefeys , Daniel Barath

Recently, 3D Gaussian Splatting (3DGS) has shown encouraging performance for open vocabulary scene understanding tasks. However, previous methods cannot distinguish 3D instance-level information, which usually predicts a heatmap between the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Hongjia Zhai , Hai Li , Zhenzhe Li , Xiaokun Pan , Yijia He , Guofeng Zhang

Recent advancements in 2D and 3D generative models have expanded the capabilities of computer vision. However, generating high-quality 4D dynamic content from a single static image remains a significant challenge. Traditional methods have…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jing Yang , Yufeng Yang

Most SLAM algorithms are based on the assumption that the scene is static. However, in practice, most scenes are dynamic which usually contains moving objects, these methods are not suitable. In this paper, we introduce DymSLAM, a dynamic…

Computer Vision and Pattern Recognition · Computer Science 2020-03-11 Chenjie Wang , Bin Luo , Yun Zhang , Qing Zhao , Lu Yin , Wei Wang , Xin Su , Yajun Wang , Chengyuan Li

Editing 4D scenes reconstructed from monocular videos based on text prompts is a valuable yet challenging task with broad applications in content creation and virtual environments. The key difficulty lies in achieving semantically precise…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Jin-Chuan Shi , Chengye Su , Jiajun Wang , Ariel Shamir , Miao Wang

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Mijeong Kim , Jongwoo Lim , Bohyung Han

Effective analysis of time series data presents significant challenges due to the complex temporal dependencies and cross-channel interactions in multivariate data. Inspired by the way human analysts visually inspect time series to uncover…

Machine Learning · Computer Science 2025-10-10 Qinghua Liu , Sam Heshmati , Zheda Mai , Zubin Abraham , John Paparrizos , Liu Ren

Existing dynamic scene reconstruction methods based on Gaussian Splatting enable real-time rendering and generate realistic images. However, adjusting the camera's focal length or the distance between Gaussian primitives and the camera to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Zilong Chen , Huan-ang Gao , Delin Qu , Haohan Chi , Hao Tang , Kai Zhang , Hao Zhao