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In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Wenhao Chai , Xun Guo , Gaoang Wang , Yan Lu

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

Depth-image-based rendering is a key view synthesis algorithm in 3D video systems, which enables the synthesis of virtual views from texture images and depth maps. An efficient view synthesis distortion estimation model is critical for…

Image and Video Processing · Electrical Eng. & Systems 2025-10-21 Chongyuan Bi , Jie Liang

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

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

Despite advancements in generating visually stunning content, video diffusion models (VDMs) often yield physically inconsistent results due to pixel-only reconstruction. To address this, we propose MMPhysVideo, the first framework to scale…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Shubo Lin , Xuanyang Zhang , Wei Cheng , Weiming Hu , Gang Yu , Jin Gao

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Leveraging text, images, structure maps, or motion trajectories as conditional guidance, diffusion models have achieved great success in automated and high-quality video generation. However, generating smooth and rational transition videos…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zuhao Yang , Jiahui Zhang , Yingchen Yu , Shijian Lu , Song Bai

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

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

Transferring appearance to 3D assets using different representations of the appearance object - such as images or text - has garnered interest due to its wide range of applications in industries like gaming, augmented reality, and digital…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Sayan Deb Sarkar , Sinisa Stekovic , Vincent Lepetit , Iro Armeni

Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often struggle with fine-grained physical consistency, exhibiting physically implausible dynamics over time.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoran Lu , Shang Wu , Jianshu Zhang , Maojiang Su , Guo Ye , Chenwei Xu , Lie Lu , Pranav Maneriker , Fan Du , Manling Li , Zhaoran Wang , Han Liu

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Michal Geyer , Omer Bar-Tal , Shai Bagon , Tali Dekel

Recent diffusion methods have made significant progress in generating videos from single images due to their powerful visual generation capabilities. However, challenges persist in image-to-video synthesis, particularly in human video…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Tiantian Wang , Chun-Han Yao , Tao Hu , Mallikarjun Byrasandra Ramalinga Reddy , Ming-Hsuan Yang , Varun Jampani

Text-to-texture generation has recently attracted increasing attention, but existing methods often suffer from the problems of view inconsistencies, apparent seams, and misalignment between textures and the underlying mesh. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Jangyeong Kim , Donggoo Kang , Junyoung Choi , Jeonga Wi , Junho Gwon , Jiun Bae , Dumim Yoon , Junghyun Han

Reconstructing general dynamic scenes is important for many computer vision and graphics applications. Recent works represent the dynamic scene with neural radiance fields for photorealistic view synthesis, while their surface geometry is…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Decai Chen , Haofei Lu , Ingo Feldmann , Oliver Schreer , Peter Eisert

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian

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

We present DreamCraft3D, a hierarchical 3D content generation method that produces high-fidelity and coherent 3D objects. We tackle the problem by leveraging a 2D reference image to guide the stages of geometry sculpting and texture…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jingxiang Sun , Bo Zhang , Ruizhi Shao , Lizhen Wang , Wen Liu , Zhenda Xie , Yebin Liu