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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

We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3D shapes and textures in under a minute. It supports…

Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D biases, resulting in compromised geometric consistency. To…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Hansheng Chen , Bokui Shen , Yulin Liu , Ruoxi Shi , Linqi Zhou , Connor Z. Lin , Jiayuan Gu , Hao Su , Gordon Wetzstein , Leonidas Guibas

We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS and edits them by using a pre-trained 2D diffusion model…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jing Wu , Jia-Wang Bian , Xinghui Li , Guangrun Wang , Ian Reid , Philip Torr , Victor Adrian Prisacariu

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

Recent advances in real-time neural rendering using point-based techniques have enabled broader adoption of 3D representations. However, foundational approaches like 3D Gaussian Splatting impose substantial storage overhead, as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhiwen Fan , Kevin Wang , Kairun Wen , Zehao Zhu , Dejia Xu , Zhangyang Wang

Recently, Gaussian splatting has demonstrated significant success in novel view synthesis. Current methods often regress Gaussians with pixel or point cloud correspondence, linking each Gaussian with a pixel or a 3D point. This leads to the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Jiamin Wu , Kenkun Liu , Han Gao , Xiaoke Jiang , Yao Yuan , Lei Zhang

3D Gaussian Splatting (3DGS) has recently emerged as a promising 3D representation. Much research has been focused on reducing its storage requirements and memory footprint. However, the needs to compress and transmit the 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yu-Ting Zhan , Cheng-Yuan Ho , Hebi Yang , Yi-Hsin Chen , Jui Chiu Chiang , Yu-Lun Liu , Wen-Hsiao Peng

Recent advancements in high-fidelity dynamic scene reconstruction have leveraged dynamic 3D Gaussians and 4D Gaussian Splatting for realistic scene representation. However, to make these methods viable for real-time applications such as…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Saqib Javed , Ahmad Jarrar Khan , Corentin Dumery , Chen Zhao , Mathieu Salzmann

While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifacts that hinder accurate spatial data exploration.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Beizhen Zhao , Yifan Zhou , Gaochao Song , Ziran Yin , Hao Wang

We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

Recent works on audio-driven talking head synthesis using Neural Radiance Fields (NeRF) have achieved impressive results. However, due to inadequate pose and expression control caused by NeRF implicit representation, these methods still…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Hongyun Yu , Zhan Qu , Qihang Yu , Jianchuan Chen , Zhonghua Jiang , Zhiwen Chen , Shengyu Zhang , Jimin Xu , Fei Wu , Chengfei Lv , Gang Yu

Text-to-3D content creation is a rapidly evolving research area. Given the scarcity of 3D data, current approaches often adapt pre-trained 2D diffusion models for 3D synthesis. Among these approaches, Score Distillation Sampling (SDS) has…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Yumin Zhang , Xingyu Miao , Haoran Duan , Bo Wei , Tejal Shah , Yang Long , Rajiv Ranjan

Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Han-Hung Lee , Manolis Savva , Angel X. Chang

Based on powerful text-to-image diffusion models, text-to-3D generation has made significant progress in generating compelling geometry and appearance. However, existing methods still struggle to recover high-fidelity object materials,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Xudong Xu , Zhaoyang Lyu , Xingang Pan , Bo Dai

Although recent advancements in text-to-3D generation have significantly improved generation quality, issues like limited level of detail and low fidelity still persist, which requires further improvement. To understand the essence of those…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Zongrui Li , Minghui Hu , Qian Zheng , Xudong Jiang

3D digital garment generation and editing play a pivotal role in fashion design, virtual try-on, and gaming. Traditional methods struggle to meet the growing demand due to technical complexity and high resource costs. Learning-based…

Graphics · Computer Science 2025-09-23 Ruiyan Wang , Zhengxue Cheng , Zonghao Lin , Jun Ling , Yuzhou Liu , Yanru An , Rong Xie , Li Song

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

Feed-forward 3D Gaussian Splatting (3DGS) has shown great promise for real-time novel view synthesis, but its application to panoramic imagery remains challenging. Existing methods often rely on multi-view cost volumes for geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Qiwei Wang , Xianghui Ze , Jingyi Yu , Yujiao Shi

Most 3D generation research focuses on up-projecting 2D foundation models into the 3D space, either by minimizing 2D Score Distillation Sampling (SDS) loss or fine-tuning on multi-view datasets. Without explicit 3D priors, these methods…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Lihe Ding , Shaocong Dong , Zhanpeng Huang , Zibin Wang , Yiyuan Zhang , Kaixiong Gong , Dan Xu , Tianfan Xue
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