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Related papers: 4K4DGen: Panoramic 4D Generation at 4K Resolution

200 papers

Recent advances in image generation have led to remarkable improvements in synthesizing perspective images. However, these models still struggle with panoramic image generation due to unique challenges, including varying levels of geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Hakan Çapuk , Andrew Bond , Muhammed Burak Kızıl , Emir Göçen , Erkut Erdem , Aykut Erdem

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

The advent of text-driven 360-degree panorama generation, enabling the synthesis of 360-degree panoramic images directly from textual descriptions, marks a transformative advancement in immersive visual content creation. This innovation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Hai Wang , Xiaoyu Xiang , Weihao Xia , Jing-Hao Xue

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

Reconstructing dynamic 3D scenes from sparse multi-view videos is highly ill-posed, often leading to geometric collapse, trajectory drift, and floating artifacts. Recent attempts introduce generative priors to hallucinate missing content,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhenlong Wu , Zihan Zheng , Xuanxuan Wang , Qianhe Wang , Hua Yang , Xiaoyun Zhang , Qiang Hu , Wenjun Zhang

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

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

Aided by text-to-image and text-to-video diffusion models, existing 4D content creation pipelines utilize score distillation sampling to optimize the entire dynamic 3D scene. However, as these pipelines generate 4D content from text or…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yuyang Yin , Dejia Xu , Zhangyang Wang , Yao Zhao , Yunchao Wei

Generating immersive 360{\deg} indoor panoramas from 2D top-down views has applications in virtual reality, interior design, real estate, and robotics. This task is challenging due to the lack of explicit 3D structure and the need for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Zitong Zhang , Suranjan Gautam , Rui Yu

Existing 4D synthesis methods primarily focus on object-level generation or dynamic scene synthesis with limited novel views, restricting their ability to generate multi-view consistent and immersive dynamic 4D scenes. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Junwei Zhou , Xueting Li , Lu Qi , Ming-Hsuan Yang

While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting…

Graphics · Computer Science 2025-10-31 Hao Feng , Hao Sun , Wei Xie , Zhi Zuo , Zhengzhe Liu

Given the high complexity of directly generating high-dimensional data such as 4D, we present 4DVD, a cascaded video diffusion model that generates 4D content in a decoupled manner. Unlike previous multi-view video methods that directly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Shuzhou Yang , Xiaodong Cun , Xiaoyu Li , Yaowei Li , Jian Zhang

Immersive applications call for synthesizing spatiotemporal 4D content from casual videos without costly 3D supervision. Existing video-to-4D methods typically rely on manually annotated camera poses, which are labor-intensive and brittle…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Dongyue Lu , Ao Liang , Tianxin Huang , Xiao Fu , Yuyang Zhao , Baorui Ma , Liang Pan , Wei Yin , Lingdong Kong , Wei Tsang Ooi , Ziwei Liu

To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recently, a field called dynamic scene video has emerged, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 In-Hwan Jin , Haesoo Choo , Seong-Hun Jeong , Heemoon Park , Junghwan Kim , Oh-joon Kwon , Kyeongbo Kong

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

In the current era of generative AI breakthroughs, generating panoramic scenes from a single input image remains a key challenge. Most existing methods use diffusion-based iterative or simultaneous multi-view inpainting. However, the lack…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Zhipeng Cai , Matthias Mueller , Reiner Birkl , Diana Wofk , Shao-Yen Tseng , JunDa Cheng , Gabriela Ben-Melech Stan , Vasudev Lal , Michael Paulitsch

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

In recent years, the demand for 3D content has grown exponentially with the intelligent upgrade of interactive media, extended reality (XR), and Metaverse industries. In order to overcome the limitations of traditional manual modeling…

Graphics · Computer Science 2025-12-23 Xiang Tang , Ruotong Li , Xiaopeng Fan

4D generation, or dynamic 3D content generation, integrates spatial, temporal, and view dimensions to model realistic dynamic scenes, playing a foundational role in advancing world models and physical AI. However, maintaining long-chain…

Graphics · Computer Science 2026-04-01 Yuanbin Man , Ying Huang , Zhile Ren , Miao Yin