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This paper explores image editing under the joint control of text and drag interactions. While recent advances in text-driven and drag-driven editing have achieved remarkable progress, they suffer from complementary limitations: text-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Qihang Wang , Yaxiong Wang , Lechao Cheng , Zhun Zhong

In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly focus on exploring strong geometry regularization. Instead,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Lue Fan , Yuxue Yang , Minxing Li , Hongsheng Li , Zhaoxiang Zhang

Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). Such solutions use GS to represent the scene's structure and the neural network to model dynamics. Such…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Joanna Kaleta , Sławomir Tadeja , Przemysław Spurek

Surgical scene simulation plays a crucial role in surgical education and simulator-based robot learning. Traditional approaches for creating these environments with surgical scene involve a labor-intensive process where designers hand-craft…

Robotics · Computer Science 2024-08-07 Zhenya Yang , Kai Chen , Yonghao Long , Qi Dou

Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS often requires a large number of primitives to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Haoran Wang , Guoxi Huang , Fan Zhang , David Bull , Nantheera Anantrasirichai

We tackle the task of learning dynamic 3D semantic radiance fields given a single monocular video as input. Our learned semantic radiance field captures per-point semantics as well as color and geometric properties for a dynamic 3D scene,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Isaac Labe , Noam Issachar , Itai Lang , Sagie Benaim

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

3D Gaussian Splatting (3DGS) has emerged as a high-fidelity and efficient paradigm for online free-viewpoint video (FVV) reconstruction, offering viewers rapid responsiveness and immersive experiences. However, existing online methods face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Jiacong Chen , Qingyu Mao , Youneng Bao , Xiandong Meng , Fanyang Meng , Ronggang Wang , Yongsheng Liang

Neural rendering methods have significantly advanced photo-realistic 3D scene rendering in various academic and industrial applications. The recent 3D Gaussian Splatting method has achieved the state-of-the-art rendering quality and speed…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Tao Lu , Mulin Yu , Linning Xu , Yuanbo Xiangli , Limin Wang , Dahua Lin , Bo Dai

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy. 3D Gaussian Splatting (3D-GS), a foundational point-based parametric 3D scene representation, models scenes as large sets of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Alex Hanson , Allen Tu , Vasu Singla , Mayuka Jayawardhana , Matthias Zwicker , Tom Goldstein

Recently, 3D Gaussian Splatting (3DGS) has become one of the mainstream methodologies for novel view synthesis (NVS) due to its high quality and fast rendering speed. However, as a point-based scene representation, 3DGS potentially…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhaoliang Zhang , Tianchen Song , Yongjae Lee , Li Yang , Cheng Peng , Rama Chellappa , Deliang Fan

3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for an explicit scene representation. Paired with a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Guikun Chen , Wenguan Wang

Rendering dynamic scenes from monocular videos is a crucial yet challenging task. The recent deformable Gaussian Splatting has emerged as a robust solution to represent real-world dynamic scenes. However, it often leads to heavily redundant…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Hanyang Kong , Xingyi Yang , Xinchao Wang

3D Gaussian Splatting (3DGS) has revolutionized real-time rendering with its state-of-the-art novel view synthesis, but its utility for accurate geometric measurement remains underutilized. Compared to multi-view stereo (MVS) point clouds…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Deyan Deng , Rongjun Qin

A key challenge in fine-grained 3D-based interactive editing is the absence of an efficient representation that balances diverse modifications with high-quality view synthesis under a given memory constraint. While 3D meshes provide…

The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large-scale 3DGS and rendering it in real-time across various…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yang Liu , He Guan , Chuanchen Luo , Lue Fan , Naiyan Wang , Junran Peng , Zhaoxiang Zhang

Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Miriam Jäger , Markus Hillemann , Boris Jutzi

Point-based image editing enables accurate and flexible control through content dragging. However, the role of text embedding during the editing process has not been thoroughly investigated. A significant aspect that remains unexplored is…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Gayoon Choi , Taejin Jeong , Sujung Hong , Seong Jae Hwang

3D affordance reasoning is essential in associating human instructions with the functional regions of 3D objects, facilitating precise, task-oriented manipulations in embodied AI. However, current methods, which predominantly depend on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zeming Wei , Junyi Lin , Yang Liu , Weixing Chen , Jingzhou Luo , Guanbin Li , Liang Lin