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Recent advancements in 3D reconstruction coupled with neural rendering techniques have greatly improved the creation of photo-realistic 3D scenes, influencing both academic research and industry applications. The technique of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Zexu Huang , Min Xu , Stuart Perry

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

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

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

Rendering and reconstruction are long-standing topics in computer vision and graphics. Achieving both high rendering quality and accurate geometry is a challenge. Recent advancements in 3D Gaussian Splatting (3DGS) have enabled…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Meng Wei , Qianyi Wu , Jianmin Zheng , Hamid Rezatofighi , Jianfei Cai

Learning 3D head priors from large 2D image collections is an important step towards high-quality 3D-aware human modeling. A core requirement is an efficient architecture that scales well to large-scale datasets and large image resolutions.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Tobias Kirschstein , Simon Giebenhain , Jiapeng Tang , Markos Georgopoulos , Matthias Nießner

Recent advances in leveraging large-scale Internet photo collections for 3D reconstruction have enabled immersive virtual exploration of landmarks and historic sites worldwide. However, little attention has been given to the immersive…

Graphics · Computer Science 2025-08-06 Yuze Wang , Yue Qi

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper introduces a novel 3D generation framework that addresses these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Yushi Lan , Shangchen Zhou , Zhaoyang Lyu , Fangzhou Hong , Shuai Yang , Bo Dai , Xingang Pan , Chen Change Loy

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

3D Language Gaussian Splatting (3DLGS) augments 3D Gaussian Splatting with language-aligned visual features for open-vocabulary 3D scene understanding. A core challenge is efficiently associating high-dimensional vision-language embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Lovre Antonio Budimir , Yushi Guan , Steve Ryhner , Sven Lončarić , Nandita Vijaykumar

Pre-training on large-scale unlabeled datasets contribute to the model achieving powerful performance on 3D vision tasks, especially when annotations are limited. However, existing rendering-based self-supervised frameworks are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Hao Liu , Minglin Chen , Yanni Ma , Haihong Xiao , Ying He

As multimodal language models advance, their application to 3D scene understanding is a fast-growing frontier, driving the development of 3D Vision-Language Models (VLMs). Current methods show strong dependence on object detectors,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Anna-Maria Halacheva , Jan-Nico Zaech , Xi Wang , Danda Pani Paudel , Luc Van Gool

We present DirectTriGS, a novel framework designed for 3D object generation with Gaussian Splatting (GS). GS-based rendering for 3D content has gained considerable attention recently. However, there has been limited exploration in directly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Xiaoliang Ju , Hongsheng Li

Score Distillation Sampling (SDS) leverages pretrained 2D diffusion models to advance text-to-3D generation but neglects multi-view correlations, being prone to geometric inconsistencies and multi-face artifacts in the generated 3D content.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Feng Yang , Wenliang Qian , Wangmeng Zuo , Hui Li

3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit methods built on Signed Distance Fields or occupancy, 3DGS lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Diego Gomez , Antoine Guédon , Nissim Maruani , Bingchen Gong , Maks Ovsjanikov
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