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Related papers: GVGEN: Text-to-3D Generation with Volumetric Repre…

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The field of text-to-3D content generation has made significant progress in generating realistic 3D objects, with existing methodologies like Score Distillation Sampling (SDS) offering promising guidance. However, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Phu Pham , Aradhya N. Mathur , Ojaswa Sharma , Aniket Bera

This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is developed to efficiently acquire feature volumes from multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Zhicong Tang , Shuyang Gu , Chunyu Wang , Ting Zhang , Jianmin Bao , Dong Chen , Baining Guo

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

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

Using the latent diffusion model has proven effective in developing novel 3D generation techniques. To harness the latent diffusion model, a key challenge is designing a high-fidelity and efficient representation that links the latent space…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Haitao Yang , Yuan Dong , Hanwen Jiang , Dejia Xu , Georgios Pavlakos , Qixing Huang

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

Most recent advances in 3D generative modeling rely on diffusion or flow-matching formulations. We instead explore a fully autoregressive alternative and introduce GaussianGPT, a transformer-based model that directly generates 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Nicolas von Lützow , Barbara Rössle , Katharina Schmid , Matthias Nießner

Video tokenization procedure is critical for a wide range of video processing tasks. Most existing approaches directly transform video into fixed-grid and patch-wise tokens, which exhibit limited versatility. Spatially, uniformly allocating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Zhenghao Chen , Zicong Chen , Lei Liu , Yiming Wu , Dong Xu

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

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

Recently, 3D Gaussian Splatting (3DGS) has enabled photorealistic view synthesis at high inference speeds. However, its splatting-based rendering model makes several approximations to the rendering equation, reducing physical accuracy. We…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Chinmay Talegaonkar , Yash Belhe , Ravi Ramamoorthi , Nicholas Antipa

Recently, high-fidelity scene reconstruction with an optimized 3D Gaussian splat representation has been introduced for novel view synthesis from sparse image sets. Making such representations suitable for applications like network…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Simon Niedermayr , Josef Stumpfegger , Rüdiger Westermann

Text-to-3D generation represents an exciting field that has seen rapid advancements, facilitating the transformation of textual descriptions into detailed 3D models. However, current progress often neglects the intricate high-order…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Donglin Di , Jiahui Yang , Chaofan Luo , Zhou Xue , Wei Chen , Xun Yang , Yue Gao

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

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Bernhard Kerbl , Andréas Meuleman , Georgios Kopanas , Michael Wimmer , Alexandre Lanvin , George Drettakis

The recent success of 3D Gaussian Splatting (3DGS) has reshaped novel view synthesis by enabling fast optimization and real-time rendering of high-quality radiance fields. However, it relies on simplified, order-dependent alpha blending and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Jan U. Müller , Robin Tim Landsgesell , Leif Van Holland , Patrick Stotko , Reinhard Klein

Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somewhat unstable, and prone to artifacts. A mitigation is to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Luke Melas-Kyriazi , Iro Laina , Christian Rupprecht , Natalia Neverova , Andrea Vedaldi , Oran Gafni , Filippos Kokkinos

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

Text-to-3D generation has shown promising results, yet common challenges such as the Multi-face Janus problem and extended generation time for high-quality assets. In this paper, we address these issues by introducing a novel three-stage…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Trapoom Ukarapol , Kevin Pruvost

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