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Sparse-view 3D reconstruction is a fundamental yet challenging task in practical 3D reconstruction applications. Recently, many methods based on the 3D Gaussian Splatting (3DGS) framework have been proposed to address sparse-view 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Lifeng Lin , Rongfeng Lu , Quan Chen , Haofan Ren , Ming Lu , Yaoqi Sun , Chenggang Yan , Anke Xue

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper, we propose leveraging multi-view depth, which represents…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Zhen Wang , Qiangeng Xu , Feitong Tan , Menglei Chai , Shichen Liu , Rohit Pandey , Sean Fanello , Achuta Kadambi , Yinda Zhang

Score Distillation Sampling (SDS) has emerged as a prevalent technique for text-to-3D generation, enabling 3D content creation by distilling view-dependent information from text-to-2D guidance. However, they frequently exhibit shortcomings…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Zeyu Cai , Duotun Wang , Yixun Liang , Zhijing Shao , Ying-Cong Chen , Xiaohang Zhan , Zeyu Wang

The increasing prominence of e-commerce has underscored the importance of Virtual Try-On (VTON). However, previous studies predominantly focus on the 2D realm and rely heavily on extensive data for training. Research on 3D VTON primarily…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Haodong Chen , Yongle Huang , Haojian Huang , Xiangsheng Ge , Dian Shao

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

Most existing video diffusion models (VDMs) are limited to mere text conditions. Thereby, they are usually lacking in control over visual appearance and geometry structure of the generated videos. This work presents Moonshot, a new video…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 David Junhao Zhang , Dongxu Li , Hung Le , Mike Zheng Shou , Caiming Xiong , Doyen Sahoo

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity. To bridge this gap, recent works have investigated multi-view diffusion but often fall short in either 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hansheng Chen , Ruoxi Shi , Yulin Liu , Bokui Shen , Jiayuan Gu , Gordon Wetzstein , Hao Su , Leonidas Guibas

Generating realistic 3D objects from single-view images requires natural appearance, 3D consistency, and the ability to capture multiple plausible interpretations of unseen regions. Existing approaches often rely on fine-tuning pretrained…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Pufan Li , Bi'an Du , Wei Hu

Recent advances in vision-language models have facilitated progress in sketch generation. However, existing specialized methods primarily focus on generic synthesis and lack mechanisms for precise control over sketch styles. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Tengjie Li , Shikui Tu , Lei Xu

Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry. Scene graphs provide a suitable…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Zhifei Yang , Keyang Lu , Chao Zhang , Jiaxing Qi , Hanqi Jiang , Ruifei Ma , Shenglin Yin , Yifan Xu , Mingzhe Xing , Zhen Xiao , Jieyi Long , Guangyao Zhai

Text-to-image generation has witnessed great progress, especially with the recent advancements in diffusion models. Since texts cannot provide detailed conditions like object appearance, reference images are usually leveraged for the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zhiqi Huang , Huixin Xiong , Haoyu Wang , Longguang Wang , Zhiheng Li

We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D geometry or mediocre rendering quality due to improper…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yuxuan Mu , Xinxin Zuo , Chuan Guo , Yilin Wang , Juwei Lu , Xiaofeng Wu , Songcen Xu , Peng Dai , Youliang Yan , Li Cheng

Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) generation, existing methods often yield subpar results,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Wei Cheng , Juncheng Mu , Xianfang Zeng , Xin Chen , Anqi Pang , Chi Zhang , Zhibin Wang , Bin Fu , Gang Yu , Ziwei Liu , Liang Pan

This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

3D Gaussian Splatting (3DGS) has demonstrated superior quality in modeling 3D objects and scenes. However, generating 3DGS remains challenging due to their discrete, unstructured, and permutation-invariant nature. In this work, we present a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Aashish Rai , Dilin Wang , Mihir Jain , Nikolaos Sarafianos , Kefan Chen , Srinath Sridhar , Aayush Prakash

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Text-guided scalable vector graphics (SVG) synthesis has broad applications in icon and sketch generation. However, existing text-to-SVG methods often suffer from limited editability, suboptimal visual quality, and low sample diversity. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Ximing Xing , Haitao Zhou , Chuang Wang , Jing Zhang , Dong Xu , Qian Yu

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

With the rising industrial attention to 3D virtual modeling technology, generating novel 3D content based on specified conditions (e.g. text) has become a hot issue. In this paper, we propose a new generative 3D modeling framework called…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Muheng Li , Yueqi Duan , Jie Zhou , Jiwen Lu