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High-quality 4D reconstruction enables photorealistic and immersive rendering of the dynamic real world. However, unlike static scenes that can be fully captured with a single camera, high-quality dynamic scenes typically require dense…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weihong Pan , Xiaoyu Zhang , Zhuang Zhang , Zhichao Ye , Nan Wang , Haomin Liu , Guofeng Zhang

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

Text-to-4D generation has recently been demonstrated viable by integrating a 2D image diffusion model with a video diffusion model. However, existing models tend to produce results with inconsistent motions and geometric structures over…

Graphics · Computer Science 2024-08-19 Ce Chen , Shaoli Huang , Xuelin Chen , Guangyi Chen , Xiaoguang Han , Kun Zhang , Mingming Gong

4D facial expression synthesizing is a critical problem in the fields of computer vision and graphics. Current methods lack flexibility and smoothness when simulating the inter-frame motion of expression sequences. In this paper, we propose…

Graphics · Computer Science 2026-03-12 Xin Lu , Chuanqing Zhuang. Zhengda Lu , Yiqun Wang , Jun Xiao

Generating high-quality 4D content from monocular videos for applications such as digital humans and AR/VR poses challenges in ensuring temporal and spatial consistency, preserving intricate details, and incorporating user guidance…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Minghao Yin , Yukang Cao , Songyou Peng , Kai Han

4D content generation aims to create dynamically evolving 3D content that responds to specific input objects such as images or 3D representations. Current approaches typically incorporate physical priors to animate 3D representations, but…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Jiajing Lin , Zhenzhong Wang , Dejun Xu , Shu Jiang , YunPeng Gong , Min Jiang

Image generation models trained on large datasets can synthesize high-quality images but often produce spatially inconsistent and distorted images due to limited information about the underlying structures and spatial layouts. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Hyundo Lee , Suhyung Choi , Inwoo Hwang , Byoung-Tak Zhang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Due to the fascinating generative performance of text-to-image diffusion models, growing text-to-3D generation works explore distilling the 2D generative priors into 3D, using the score distillation sampling (SDS) loss, to bypass the data…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yu-Jie Yuan , Leif Kobbelt , Jiwen Liu , Yuan Zhang , Pengfei Wan , Yu-Kun Lai , Lin Gao

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of text-to-4D dynamic 3D scene generation with diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Yufeng Zheng , Xueting Li , Koki Nagano , Sifei Liu , Karsten Kreis , Otmar Hilliges , Shalini De Mello

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

We propose the first framework capable of computing a 4D spatio-temporal grid of video frames and 3D Gaussian particles for each time step using a feed-forward architecture. Our architecture has two main components, a 4D video model and a…

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

Remarkable advances in recent 2D image and 3D shape generation have induced a significant focus on dynamic 4D content generation. However, previous 4D generation methods commonly struggle to maintain spatial-temporal consistency and adapt…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Mengmeng Liu , Jiuming Liu , Yunpeng Zhang , Jiangtao Li , Michael Ying Yang , Francesco Nex , Hao Cheng

4D mesh generation has recently emerged as a powerful paradigm for recovering dynamic 3D structure from videos, but existing methods remain slow, computationally expensive, and difficult to scale to longer sequences. We introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Dvir Samuel , Yuval Atzmon , Gal Chechik , Yoni Kasten

Advances in generative modeling have significantly enhanced digital content creation, extending from 2D images to complex 3D and 4D scenes. Despite substantial progress, producing high-fidelity and temporally consistent dynamic 4D content…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 DongFu Yin , Xiaotian Chen , Fei Richard Yu , Xuanchen Li , Xinhao Zhang

This paper targets high-fidelity and real-time view synthesis of dynamic 3D scenes at 4K resolution. Recently, some methods on dynamic view synthesis have shown impressive rendering quality. However, their speed is still limited when…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Zhen Xu , Sida Peng , Haotong Lin , Guangzhao He , Jiaming Sun , Yujun Shen , Hujun Bao , Xiaowei Zhou

With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in 4D generative modeling, existing methods exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Eddie Pokming Sheung , Qihao Liu , Wufei Ma , Prakhar Kaushik , Jianwen Xie , Alan Yuille

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camera motions. Existing methods either hallucinate inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Liao Shen , Xingyi Li , Huiqiang Sun , Juewen Peng , Ke Xian , Zhiguo Cao , Guosheng Lin

Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive approach is to extend previous image-to-3D pipelines by transferring off-the-shelf image generation models such as score…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Zijie Pan , Zeyu Yang , Xiatian Zhu , Li Zhang