English
Related papers

Related papers: GradeADreamer: Enhanced Text-to-3D Generation Usin…

200 papers

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

Recent methods such as Score Distillation Sampling (SDS) and Variational Score Distillation (VSD) using 2D diffusion models for text-to-3D generation have demonstrated impressive generation quality. However, the long generation time of such…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Linqi Zhou , Andy Shih , Chenlin Meng , Stefano Ermon

With the onset of diffusion-based generative models and their ability to generate text-conditioned images, content generation has received a massive invigoration. Recently, these models have been shown to provide useful guidance for the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Alexander Vilesov , Pradyumna Chari , Achuta Kadambi

To address the data scarcity associated with 3D assets, 2D-lifting techniques such as Score Distillation Sampling (SDS) have become a widely adopted practice in text-to-3D generation pipelines. However, the diffusion models used in these…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Utkarsh Nath , Rajeev Goel , Eun Som Jeon , Changhoon Kim , Kyle Min , Yezhou Yang , Yingzhen Yang , Pavan Turaga

Traditional 3D garment creation is labor-intensive, involving sketching, modeling, UV mapping, and texturing, which are time-consuming and costly. Recent advances in diffusion-based generative models have enabled new possibilities for 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Boqian Li , Xuan Li , Ying Jiang , Tianyi Xie , Feng Gao , Huamin Wang , Yin Yang , Chenfanfu Jiang

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-faced geometry, primarily due to the intrinsically noisy nature…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Pengsheng Guo , Hans Hao , Adam Caccavale , Zhongzheng Ren , Edward Zhang , Qi Shan , Aditya Sankar , Alexander G. Schwing , Alex Colburn , Fangchang Ma

Generating lifelike 3D humans from a single RGB image remains a challenging task in computer vision, as it requires accurate modeling of geometry, high-quality texture, and plausible unseen parts. Existing methods typically use multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Zhibin Liu , Haoye Dong , Aviral Chharia , Hefeng Wu

While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address this issue, we propose a two-stage approach named Hunyuan3D…

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

Recent advances in text-to-image diffusion models have been driven by the increasing availability of paired 2D data. However, the development of 3D diffusion models has been hindered by the scarcity of high-quality 3D data, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Tiange Xiang , Kai Li , Chengjiang Long , Christian Häne , Peihong Guo , Scott Delp , Ehsan Adeli , Li Fei-Fei

The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yixun Liang , Xin Yang , Jiantao Lin , Haodong Li , Xiaogang Xu , Yingcong Chen

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

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Recent developments in 3D reconstruction and neural rendering have significantly propelled the capabilities of photo-realistic 3D scene rendering across various academic and industrial fields. The 3D Gaussian Splatting technique, alongside…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zexu Huang , Min Xu , Stuart Perry

Despite recent advances in text-to-3D generation techniques, current methods often suffer from geometric inconsistencies, commonly referred to as the Janus Problem. This paper identifies the root cause of the Janus Problem: viewpoint…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Qing Zhang , Jinguang Tong , Jing Zhang , Jie Hong , Xuesong Li

3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has achieved high-quality reconstruction and real-time rendering of complex scenes. However, the rasterization pipeline still suffers from unnecessary overhead…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Xinzhe Wang , Ran Yi , Lizhuang Ma

Dense colored point clouds enhance visual perception and are of significant value in various robotic applications. However, existing learning-based point cloud upsampling methods are constrained by computational resources and batch…

Robotics · Computer Science 2024-09-04 Zixuan Guo , Yifan Xie , Weijing Xie , Peng Huang , Fei Ma , Fei Richard Yu