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Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

We propose PoseGaussian, a pose-guided Gaussian Splatting framework for high-fidelity human novel view synthesis. Human body pose serves a dual purpose in our design: as a structural prior, it is fused with a color encoder to refine depth…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Ju Shen , Chen Chen , Tam V. Nguyen , Vijayan K. Asari

With the rapid advancements in diffusion models and 3D generation techniques, dynamic 3D content generation has become a crucial research area. However, achieving high-fidelity 4D (dynamic 3D) generation with strong spatial-temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Jinwei Li , Huan-ang Gao , Wenyi Li , Haohan Chi , Chenyu Liu , Chenxi Du , Yiqian Liu , Mingju Gao , Guiyu Zhang , Zongzheng Zhang , Li Yi , Yao Yao , Jingwei Zhao , Hongyang Li , Yikai Wang , Hao Zhao

Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3D Gaussian Splatting (3DGS) with SLAM to achieve both robust camera pose estimation and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Yunsong Wang , Gim Hee Lee

3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage requirements and inherently unstructured representation pose challenges for deployment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuqin Lu , Yang Zhou , Yihua Dai , Guiqing Li , Shengfeng He

Recently, Gaussian Splatting methods have emerged as a desirable substitute for prior Radiance Field methods for novel-view synthesis of scenes captured with multi-view images or videos. In this work, we propose a novel extension to 4D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Karly Hou , Wanhua Li , Hanspeter Pfister

We consider the problem of novel view synthesis from unposed images in a single feed-forward. Our framework capitalizes on fast speed, scalability, and high-quality 3D reconstruction and view synthesis capabilities of 3DGS, where we further…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Sunghwan Hong , Jaewoo Jung , Heeseong Shin , Jisang Han , Jiaolong Yang , Chong Luo , Seungryong Kim

Learning 4D language fields to enable time-sensitive, open-ended language queries in dynamic scenes is essential for many real-world applications. While LangSplat successfully grounds CLIP features into 3D Gaussian representations,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Wanhua Li , Renping Zhou , Jiawei Zhou , Yingwei Song , Johannes Herter , Minghan Qin , Gao Huang , Hanspeter Pfister

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

We present ViewSplat, a view-adaptive 3D Gaussian splatting network for novel view synthesis from unposed images. While recent feed-forward 3D Gaussian splatting has significantly accelerated 3D scene reconstruction by bypassing per-scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Moonyeon Jeong , Seunggi Min , Suhyeon Lee , Hongje Seong

3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requires dense training views to accurately reconstruct 3D geometry. A limited number of input…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Haolin Xiong , Sairisheek Muttukuru , Rishi Upadhyay , Pradyumna Chari , Achuta Kadambi

Novel view synthesis from a sparse set of input images is a challenging problem of great practical interest, especially when camera poses are absent or inaccurate. Direct optimization of camera poses and usage of estimated depths in neural…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Kaiwen Jiang , Yang Fu , Mukund Varma T , Yash Belhe , Xiaolong Wang , Hao Su , Ravi Ramamoorthi

Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive approach is to extend previous image-to-3D pipelines by transferring off-the-shelf image generation models such as score…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Zijie Pan , Zeyu Yang , Xiatian Zhu , Li Zhang

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

Recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated its potential for efficient and photorealistic 3D reconstructions, which is crucial for diverse applications such as robotics and immersive media. However, current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Daheng Yin , Isaac Ding , Yili Jin , Jianxin Shi , Jiangchuan Liu

Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-Gaussian or voxel-to-Gaussian pipelines that uniformly allocate Gaussians, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Injae Kim , Chaehyeon Kim , Minseong Bae , Minseok Joo , Hyunwoo J. Kim

Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain limited under aerial conditions with single-view capture, wide spatial range, and dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Hanyang Liu , Rongjun Qin

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng