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Related papers: L3DG: Latent 3D Gaussian Diffusion

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4D content generation has achieved remarkable progress recently. However, existing methods suffer from long optimization times, a lack of motion controllability, and a low quality of details. In this paper, we introduce DreamGaussian4D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Jiawei Ren , Liang Pan , Jiaxiang Tang , Chi Zhang , Ang Cao , Gang Zeng , Ziwei Liu

Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent Video Diffusion Models (LVDMs) offer promising 3D priors…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yabo Chen , Chen Yang , Jiemin Fang , Xiaopeng Zhang , Lingxi Xie , Wei Shen , Wenrui Dai , Hongkai Xiong , Qi Tian

With the widespread usage of VR devices and contents, demands for 3D scene generation techniques become more popular. Existing 3D scene generation models, however, limit the target scene to specific domain, primarily due to their training…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jaeyoung Chung , Suyoung Lee , Hyeongjin Nam , Jaerin Lee , Kyoung Mu Lee

Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus on the underexplored text-to-4D setting and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Huan Ling , Seung Wook Kim , Antonio Torralba , Sanja Fidler , Karsten Kreis

Flow matching and diffusion models have shown impressive results in text-to-image generation, producing photorealistic images through an iterative denoising process. A common strategy to speed up synthesis is to perform early denoising at…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Jyun-Ze Tang , Chih-Fan Hsu , Jeng-Lin Li , Ming-Ching Chang , Wei-Chao Chen

Traditional 3D content representations include dense point clouds that consume large amounts of data and hence network bandwidth, while newer representations such as neural radiance fields suffer from poor frame rates due to their…

Graphics · Computer Science 2025-04-09 Yi-Zhen Tsai , Xuechen Zhang , Zheng Li , Jiasi Chen

Recently single-view 3D generation via Gaussian splatting has emerged and developed quickly. They learn 3D Gaussians from 2D RGB images generated from pre-trained multi-view diffusion (MVD) models, and have shown a promising avenue for 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yiyang Shen , Kun Zhou , He Wang , Yin Yang , Tianjia Shao

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

We present Turbo3D, an ultra-fast text-to-3D system capable of generating high-quality Gaussian splatting assets in under one second. Turbo3D employs a rapid 4-step, 4-view diffusion generator and an efficient feed-forward Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Hanzhe Hu , Tianwei Yin , Fujun Luan , Yiwei Hu , Hao Tan , Zexiang Xu , Sai Bi , Shubham Tulsiani , Kai Zhang

We present a cascaded diffusion model based on a part-level implicit 3D representation. Our model achieves state-of-the-art generation quality and also enables part-level shape editing and manipulation without any additional training in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Juil Koo , Seungwoo Yoo , Minh Hieu Nguyen , Minhyuk Sung

3D Gaussian Splatting (3DGS) has exhibited remarkable efficacy in novel view synthesis (NVS). However, it suffers from a significant drawback: achieving high-fidelity rendering typically necessitates a large number of 3D Gaussians,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Lintao Xiang , Xinkai Chen , Jianhuang Lai , Guangcong Wang

AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models have been made in this area, the visual quality and length…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yingqing He , Tianyu Yang , Yong Zhang , Ying Shan , Qifeng Chen

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

Generating ground-level views and coherent 3D site models from aerial-only imagery is challenging due to extreme viewpoint changes, missing intermediate observations, and large scale variations. Existing methods either refine renderings…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Sirshapan Mitra , Yogesh S. Rawat

One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and…

Graphics · Computer Science 2024-05-31 Artur Kasymov , Bartosz Czekaj , Marcin Mazur , Jacek Tabor , Przemysław Spurek

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

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

n this work, we propose a latent molecular diffusion model that can make the generated 3D molecules rich in diversity and maintain rich geometric features. The model captures the information of the forces and local constraints between atoms…

Machine Learning · Computer Science 2024-12-06 Xiang Chen

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

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun
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