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Related papers: 2D-Guided 3D Gaussian Segmentation

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The recent advances in 3D Gaussian Splatting (3DGS) show promising results on the novel view synthesis (NVS) task. With its superior rendering performance and high-fidelity rendering quality, 3DGS is excelling at its previous NeRF…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yu Chen , Gim Hee Lee

Three-dimensional Ultrasound image segmentation methods are surveyed in this paper. The focus of this report is to investigate applications of these techniques and a review of the original ideas and concepts. Although many two-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2016-11-30 Mohammad Hamed Mozaffari , WonSook Lee

Reconstructing and segmenting scenes from unconstrained photo collections obtained from the Internet is a novel but challenging task. Unconstrained photo collections are easier to get than well-captured photo collections. These…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Yongtang Bao , Chengjie Tang , Yuze Wang , Haojie Li

3D Gaussian Splatting (3DGS) has begun incorporating rich information from 2D foundation models. However, most approaches rely on a bottom-up optimization process that treats raw 2D features as ground truth, incurring increased…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hyunjoon Lee , Joonkyu Min , Jaesik Park

The efficient rendering and explicit nature of 3DGS promote the advancement of 3D scene manipulation. However, existing methods typically encounter challenges in controlling the manipulation region and are unable to furnish the user with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Yian Zhao , Wanshi Xu , Ruochong Zheng , Pengchong Qiao , Chang Liu , Jie Chen

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

Open-vocabulary querying in 3D space is challenging but essential for scene understanding tasks such as object localization and segmentation. Language-embedded scene representations have made progress by incorporating language features into…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Jin-Chuan Shi , Miao Wang , Hao-Bin Duan , Shao-Hua Guan

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for neural scene reconstruction, offering high-quality novel view synthesis while maintaining computational efficiency. In this paper, we extend the capabilities of 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Jens Piekenbrinck , Christian Schmidt , Alexander Hermans , Narunas Vaskevicius , Timm Linder , Bastian Leibe

Panoptic segmentation of 3D scenes, involving the segmentation and classification of object instances in a dense 3D reconstruction of a scene, is a challenging problem, especially when relying solely on unposed 2D images. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Lojze Zust , Yohann Cabon , Juliette Marrie , Leonid Antsfeld , Boris Chidlovskii , Jerome Revaud , Gabriela Csurka

Multimodal referring segmentation aims to segment target objects in visual scenes, such as images, videos, and 3D scenes, based on referring expressions in text or audio format. This task plays a crucial role in practical applications…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Henghui Ding , Song Tang , Shuting He , Chang Liu , Zuxuan Wu , Yu-Gang Jiang

3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometric priors. Existing methods have explored predicting point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Kanle Shi , Shenkun Xu , Yi Fang , Yu-Shen Liu

Part segmentation and motion estimation are two fundamental problems for articulated object motion analysis. In this paper, we present a method to solve these two problems jointly from a sequence of observed point clouds of a single…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Jun-Jee Chao , Qingyuan Jiang , Volkan Isler

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

User-friendly 3D object editing is a challenging task that has attracted significant attention recently. The limitations of direct 3D object editing without 2D prior knowledge have prompted increased attention towards utilizing 2D…

Graphics · Computer Science 2024-05-10 Sitian Shen , Jing Xu , Yuheng Yuan , Xingyi Yang , Qiuhong Shen , Xinchao Wang

Achieving a consistent and compact 3D segmentation field is crucial for maintaining semantic coherence across views and accurately representing scene structures. Previous 3D scene segmentation methods rely on video segmentation models to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Wenhao Hu , Wenhao Chai , Shengyu Hao , Xiaotong Cui , Xuexiang Wen , Jenq-Neng Hwang , Gaoang Wang

Open-vocabulary 3D panoptic segmentation has recently emerged as a significant trend. Top-performing methods currently integrate 2D segmentation with geometry-aware 3D primitives. However, the advantage would be lost without high-fidelity…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Feng Xue , Wenzhuang Xu , Guofeng Zhong , Anlong Minga , Nicu Sebe

Open-vocabulary 3D scene understanding is crucial for applications requiring natural language-driven spatial interpretation, such as robotics and augmented reality. While 3D Gaussian Splatting (3DGS) offers a powerful representation for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Wei Sun , Yanzhao Zhou , Jianbin Jiao , Yuan Li

Neural Radiance Fields (NeRFs) have emerged as a popular approach for novel view synthesis. While NeRFs are quickly being adapted for a wider set of applications, intuitively editing NeRF scenes is still an open challenge. One important…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Ashkan Mirzaei , Tristan Aumentado-Armstrong , Konstantinos G. Derpanis , Jonathan Kelly , Marcus A. Brubaker , Igor Gilitschenski , Alex Levinshtein

The recently developed Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have shown encouraging and impressive results for visual SLAM. However, most representative methods require RGBD sensors and are only available for indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Zhe Xin , Chenyang Wu , Penghui Huang , Yanyong Zhang , Yinian Mao , Guoquan Huang

Recent advances in Neural Radiance Fields (NeRF) boast impressive performances for generative tasks such as novel view synthesis and 3D reconstruction. Methods based on neural radiance fields are able to represent the 3D world implicitly by…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Jesus Zarzar , Sara Rojas , Silvio Giancola , Bernard Ghanem