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

200 papers

Images and videos are discrete 2D projections of the 4D world (3D space + time). Most visual understanding, prediction, and generation operate directly on 2D observations, leading to suboptimal performance. We propose SeeU, a novel approach…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yu Yuan , Tharindu Wickremasinghe , Zeeshan Nadir , Xijun Wang , Yiheng Chi , Stanley H. Chan

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

Video-conditioned 4D shape generation aims to recover time-varying 3D geometry and view-consistent appearance directly from an input video. In this work, we introduce a native video-to-4D shape generation framework that synthesizes a single…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiraphon Yenphraphai , Ashkan Mirzaei , Jianqi Chen , Jiaxu Zou , Sergey Tulyakov , Raymond A. Yeh , Peter Wonka , Chaoyang Wang

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality 4D objects. Previous methods generally rely on score…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qi Sun , Zhiyang Guo , Ziyu Wan , Jing Nathan Yan , Shengming Yin , Wengang Zhou , Jing Liao , Houqiang Li

Omnidirectional and 360{\deg} images are becoming widespread in industry and in consumer society, causing omnidirectional computer vision to gain attention. Their wide field of view allows the gathering of a great amount of information…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Bruno Berenguel-Baeta , Jesus Bermudez-Cameo , Jose J. Guerrero

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such as deformation models or time-dependent neural…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Sherwin Bahmani , Xian Liu , Wang Yifan , Ivan Skorokhodov , Victor Rong , Ziwei Liu , Xihui Liu , Jeong Joon Park , Sergey Tulyakov , Gordon Wetzstein , Andrea Tagliasacchi , David B. Lindell

Recent single-view 3D generative methods have made significant advancements by leveraging knowledge distilled from extensive 3D object datasets. However, challenges persist in the synthesis of 3D scenes from a single view, primarily due to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Guo Pu , Yiming Zhao , Zhouhui Lian

Recent 3D feed-forward models, such as the Visual Geometry Grounded Transformer (VGGT), have shown strong capability in inferring 3D attributes of static scenes. However, since they are typically trained on static datasets, these models…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Kaichen Zhou , Yuhan Wang , Grace Chen , Xinhai Chang , Gaspard Beaudouin , Fangneng Zhan , Paul Pu Liang , Mengyu Wang

Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Rui Song , Chenwei Liang , Yan Xia , Walter Zimmer , Hu Cao , Holger Caesar , Andreas Festag , Alois Knoll

Omnidirectional vision, using 360-degree vision to understand the environment, has become increasingly critical across domains like robotics, industrial inspection, and environmental monitoring. Compared to traditional pinhole vision,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Xu Zheng , Chenfei Liao , Ziqiao Weng , Kaiyu Lei , Zihao Dongfang , Haocong He , Yuanhuiyi Lyu , Lutao Jiang , Lu Qi , Li Chen , Danda Pani Paudel , Kailun Yang , Linfeng Zhang , Luc Van Gool , Xuming Hu

In this paper, we present PanoDreamer, a novel method for producing a coherent 360{\deg} 3D scene from a single input image. Unlike existing methods that generate the scene sequentially, we frame the problem as single-image panorama and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Avinash Paliwal , Xilong Zhou , Andrii Tsarov , Nima Khademi Kalantari

Scene-level 3D generation represents a critical frontier in multimedia and computer graphics, yet existing approaches either suffer from limited object categories or lack editing flexibility for interactive applications. In this paper, we…

Graphics · Computer Science 2025-04-18 Wenqi Dong , Bangbang Yang , Zesong Yang , Yuan Li , Tao Hu , Hujun Bao , Yuewen Ma , Zhaopeng Cui

Modeling dynamic 3D scenes is challenging due to their high-dimensional nature, which requires aggregating information from multiple views to reconstruct time-evolving 3D geometry and motion. We present a novel multi-video 4D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yonghan Lee , Tsung-Wei Huang , Shiv Gehlot , Jaehoon Choi , Guan-Ming Su , Dinesh Manocha

Panoramic image stitching provides a unified, wide-angle view of a scene that extends beyond the camera's field of view. Stitching frames of a panning video into a panoramic photograph is a well-understood problem for stationary scenes, but…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Jingwei Ma , Erika Lu , Roni Paiss , Shiran Zada , Aleksander Holynski , Tali Dekel , Brian Curless , Michael Rubinstein , Forrester Cole

Transforming casually captured, monocular videos into fully immersive dynamic experiences is a highly ill-posed task, and comes with significant challenges, e.g., reconstructing unseen regions, and dealing with the ambiguity in monocular…

Graphics · Computer Science 2026-04-08 Denis Rozumny , Jonathon Luiten , Numair Khan , Johannes Schönberger , Peter Kontschieder

Generating complete 360-degree panoramas from narrow field of view images is ongoing research as omnidirectional RGB data is not readily available. Existing GAN-based approaches face some barriers to achieving higher quality output, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Tianhao Wu , Chuanxia Zheng , Tat-Jen Cham

Lifting perspective images and videos to 360{\deg} panoramas enables immersive 3D world generation. Existing approaches often rely on explicit geometric alignment between the perspective and the equirectangular projection (ERP) space. Yet,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Ziyi Wu , Daniel Watson , Andrea Tagliasacchi , David J. Fleet , Marcus A. Brubaker , Saurabh Saxena

Vision-and-Language Navigation (VLN) requires the agent to follow language instructions to navigate through 3D environments. One main challenge in VLN is the limited availability of photorealistic training environments, which makes it hard…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Jialu Li , Mohit Bansal

Generating high-quality 360{\deg} panoramic videos remains a significant challenge due to the fundamental differences between panoramic and traditional perspective-view projections. While perspective videos rely on a single viewpoint with a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Zeyu Dong , Yuyang Yin , Yuqi Li , Eric Li , Hao-Xiang Guo , Yikai Wang
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