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Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating…

Graphics · Computer Science 2025-10-07 Nilay Kumar , Priyansh Bhandari , G. Maragatham

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1) multi-view inconsistency often leads to style conflicts,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Yitong Yang , Yinglin Wang , Changshuo Wang , Huajie Wang , Shuting He

Generating 3D faces from textual descriptions has a multitude of applications, such as gaming, movie, and robotics. Recent progresses have demonstrated the success of unconditional 3D face generation and text-to-3D shape generation.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Cuican Yu , Guansong Lu , Yihan Zeng , Jian Sun , Xiaodan Liang , Huibin Li , Zongben Xu , Songcen Xu , Wei Zhang , Hang Xu

Recent advances in 2D image generation have achieved remarkable quality,largely driven by the capacity of diffusion models and the availability of large-scale datasets. However, direct 3D generation is still constrained by the scarcity and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Xuyi Meng , Chen Wang , Jiahui Lei , Kostas Daniilidis , Jiatao Gu , Lingjie Liu

Text-to-3D synthesis has recently seen intriguing advances by combining the text-to-image priors with 3D representation methods, e.g., 3D Gaussian Splatting (3D GS), via Score Distillation Sampling (SDS). However, a hurdle of existing…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Lutao Jiang , Xu Zheng , Yuanhuiyi Lyu , Jiazhou Zhou , Lin Wang

We present Stable Video 3D (SV3D) -- a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D generation propose techniques to adapt 2D generative models for…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Vikram Voleti , Chun-Han Yao , Mark Boss , Adam Letts , David Pankratz , Dmitry Tochilkin , Christian Laforte , Robin Rombach , Varun Jampani

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

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie

This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engineering design synthesis. Our model proposes parametric,…

Artificial Intelligence · Computer Science 2024-12-09 Rui Zhou , Yanxia Zhang , Chenyang Yuan , Frank Permenter , Nikos Arechiga , Matt Klenk , Faez Ahmed

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 demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D representation, bridging the gap between point clouds and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Wenyuan Zhang , Yu-Shen Liu

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

We present DIRECT-3D, a diffusion-based 3D generative model for creating high-quality 3D assets (represented by Neural Radiance Fields) from text prompts. Unlike recent 3D generative models that rely on clean and well-aligned 3D data,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Qihao Liu , Yi Zhang , Song Bai , Adam Kortylewski , Alan Yuille

The significance of informative and robust point representations has been widely acknowledged for 3D scene understanding. Despite existing self-supervised pre-training counterparts demonstrating promising performance, the model collapse and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Lei Yao , Yi Wang , Yi Zhang , Moyun Liu , Lap-Pui Chau

One image to editable dynamic 3D model and video generation is novel direction and change in the research area of single image to 3D representation or 3D reconstruction of image. Gaussian Splatting has demonstrated its advantages in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

Multi-view generation with camera pose control and prompt-based customization are both essential elements for achieving controllable generative models. However, existing multi-view generation models do not support customization with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Minjung Shin , Hyunin Cho , Sooyeon Go , Jin-Hwa Kim , Youngjung Uh

Recent advancements in Text-to-3D modeling have shown significant potential for the creation of 3D content. However, due to the complex geometric shapes of objects in the natural world, generating 3D content remains a challenging task.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Huanning Dong , Fan Li , Ping Kuang , Jianwen Min

In recent years, significant progress has been made in the development of text-to-image generation models. However, these models still face limitations when it comes to achieving full controllability during the generation process. Often,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Salaheldin Mohamed

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi
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