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While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especially for view information. This limitation leads to the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Zhipeng Hu , Minda Zhao , Chaoyi Zhao , Xinyue Liang , Lincheng Li , Zeng Zhao , Changjie Fan , Xiaowei Zhou , Xin Yu

The rapid progress of large, pretrained models for both visual content generation and 3D reconstruction opens up new possibilities for text-to-3D generation. Intuitively, one could obtain a formidable 3D scene generator if one were able to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Hyojun Go , Dominik Narnhofer , Goutam Bhat , Prune Truong , Federico Tombari , Konrad Schindler

The creation of high-quality 3D assets is paramount for applications in digital heritage preservation, entertainment, and robotics. Traditionally, this process necessitates skilled professionals and specialized software for the modeling,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Shen Chen , Jiale Zhou , Zhongyu Jiang , Tianfang Zhang , Zongkai Wu , Jenq-Neng Hwang , Lei Li

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

Recent advancements in 3D generation have leveraged synthetic datasets with ground truth 3D assets and predefined cameras. However, the potential of adopting real-world datasets, which can produce significantly more realistic 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Xinyang Li , Zhangyu Lai , Linning Xu , Yansong Qu , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

The convergence of generative artificial intelligence and advanced computer vision technologies introduces a groundbreaking approach to transforming textual descriptions into three-dimensional representations. This research proposes a fully…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Venkat Kumar R , Deepak Saravanan

We present a novel approach for enhancing the resolution and geometric fidelity of 3D Gaussian Splatting (3DGS) beyond native training resolution. Current 3DGS methods are fundamentally limited by their input resolution, producing…

Graphics · Computer Science 2025-06-10 Shuja Khalid , Mohamed Ibrahim , Yang Liu

Most advances in 3D Generative Adversarial Networks (3D GANs) largely depend on ray casting-based volume rendering, which incurs demanding rendering costs. One promising alternative is rasterization-based 3D Gaussian Splatting (3D-GS),…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Sangeek Hyun , Jae-Pil Heo

Image-based 3D scene reconstruction, which transforms multi-view images into a structured 3D representation of the surrounding environment, is a common task across many modern applications. 3D Gaussian Splatting (3DGS) is a new paradigm to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Md Musfiqur Rahman Sanim , Zhihao Shu , Bahram Afsharmanesh , AmirAli Mirian , Jiexiong Guan , Wei Niu , Bin Ren , Gagan Agrawal

We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model. Given the noisy multi-view latents, the 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Xinyang Li , Zhangyu Lai , Linning Xu , Jianfei Guo , Liujuan Cao , Shengchuan Zhang , Bo Dai , Rongrong Ji

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

Recently, image-to-3D approaches have significantly advanced the generation quality and speed of 3D assets based on large reconstruction models, particularly 3D Gaussian reconstruction models. Existing large 3D Gaussian models directly map…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Longfei Lu , Huachen Gao , Tao Dai , Yaohua Zha , Zhi Hou , Junta Wu , Shu-Tao Xia

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

3D Gaussian Splatting (3DGS) has emerged as a novel explicit representation for 3D scenes, offering both high-fidelity reconstruction and efficient rendering. However, 3DGS lacks 3D segmentation ability, which limits its applicability in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Yupeng Zhang , Dezhi Zheng , Ping Lu , Han Zhang , Lei Wang , Liping xiang , Cheng Luo , Kaijun Deng , Xiaowen Fu , Linlin Shen , Jinbao Wang

3D Gaussian Splatting (3DGS) has emerged as a revolutionary 3D representation. However, its substantial data size poses a major barrier to widespread adoption. While feed-forward 3DGS compression offers a practical alternative to costly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zhening Liu , Rui Song , Yushi Huang , Yingdong Hu , Xinjie Zhang , Jiawei Shao , Zehong Lin , Jun Zhang

While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning. This heavily restricts the degree of control over generated objects as well as the possible applications…

Computer Vision and Pattern Recognition · Computer Science 2020-10-26 Dario Pavllo , Graham Spinks , Thomas Hofmann , Marie-Francine Moens , Aurelien Lucchi

In this work, we introduce Prometheus, a 3D-aware latent diffusion model for text-to-3D generation at both object and scene levels in seconds. We formulate 3D scene generation as multi-view, feed-forward, pixel-aligned 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Yuanbo Yang , Jiahao Shao , Xinyang Li , Yujun Shen , Andreas Geiger , Yiyi Liao

We introduce GaussianZoom, a generative zoom-in 3D reconstruction system with an iterative progressive framework that combines geometry-consistent scene modeling and multi-scale semantic reasoning to enable high-fidelity extreme zoom-in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiale Shi , Jiarui Hu , Zesong Yang , Kaixuan Luan , Hujun Bao , Zhaopeng Cui
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