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Related papers: DreamGaussian4D: Generative 4D Gaussian Splatting

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3D Gaussian Splatting (3DGS) has recently gained popularity for efficient scene rendering by representing scenes as explicit sets of anisotropic 3D Gaussians. However, most existing work focuses primarily on modeling external surfaces. In…

Image and Video Processing · Electrical Eng. & Systems 2026-01-12 Shuxin Liang , Yihan Xiao , Wenlu Tang

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 introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhibit substantial appearance variations from different…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jiayue Liu , Xiao Tang , Freeman Cheng , Roy Yang , Zhihao Li , Jianzhuang Liu , Yi Huang , Jiaqi Lin , Shiyong Liu , Xiaofei Wu , Songcen Xu , Chun Yuan

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

In recent times, the generation of 3D assets from text prompts has shown impressive results. Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts. 3D diffusion models have good 3D consistency, but their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Taoran Yi , Jiemin Fang , Junjie Wang , Guanjun Wu , Lingxi Xie , Xiaopeng Zhang , Wenyu Liu , Qi Tian , Xinggang Wang

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate the initial layout and introduce a layout-guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Xiaoyu Zhou , Xingjian Ran , Yajiao Xiong , Jinlin He , Zhiwei Lin , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

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 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

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

We present Free4D, a novel tuning-free framework for 4D scene generation from a single image. Existing methods either focus on object-level generation, making scene-level generation infeasible, or rely on large-scale multi-view video…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Tianqi Liu , Zihao Huang , Zhaoxi Chen , Guangcong Wang , Shoukang Hu , Liao Shen , Huiqiang Sun , Zhiguo Cao , Wei Li , Ziwei Liu

We propose L3DG, the first approach for generative 3D modeling of 3D Gaussians through a latent 3D Gaussian diffusion formulation. This enables effective generative 3D modeling, scaling to generation of entire room-scale scenes which can be…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Barbara Roessle , Norman Müller , Lorenzo Porzi , Samuel Rota Bulò , Peter Kontschieder , Angela Dai , Matthias Nießner

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling scenes affected by transient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chuanyu Fu , Yuqi Zhang , Kunbin Yao , Guanying Chen , Yuan Xiong , Chuan Huang , Shuguang Cui , Xiaochun Cao

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

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

Reliable autonomous driving relies on large-scale, well-labeled data and robust models. However, manual data collection is resource-intensive, and traditional simulation suffers from a persistent reality gap. While recent generative…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Kaicong Huang , Talha Azfar , Weisong Shi , Ruimin Ke
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