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Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely either on explicitly constructing 3D geometry, which suffers…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jia Li , Han Yan , Yihang Chen , Siqi Li , Xibin Song , Yifu Wang , Jianfei Cai , Tien-Tsin Wong , Pan Ji

Existing diffusion-based 3D scene generation methods primarily operate in 2D image/video latent spaces, which makes maintaining cross-view appearance and geometric consistency inherently challenging. To bridge this gap, we present OneWorld,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Sensen Gao , Zhaoqing Wang , Qihang Cao , Dongdong Yu , Changhu Wang , Tongliang Liu , Mingming Gong , Jiawang Bian

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Shijie Zhou , Zhiwen Fan , Dejia Xu , Haoran Chang , Pradyumna Chari , Tejas Bharadwaj , Suya You , Zhangyang Wang , Achuta Kadambi

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

We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrically impoverished input one could offer a multi-view generator. They convey scene intent…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Ahmed Bourouis , Savas Ozkan , Andrea Maracani , Yi-Zhe Song , Mete Ozay

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

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Mijeong Kim , Jongwoo Lim , Bohyung Han

We address the challenge of recovering an underlying scene geometry and colors from a sparse set of RGBD view observations. In this work, we present a new solution termed RGBD$^2$ that sequentially generates novel RGBD views along a camera…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Jiabao Lei , Jiapeng Tang , Kui Jia

While the generation of 3D content from single-view images has been extensively studied, the creation of physically consistent 3D dynamic scenes from videos remains in its early stages. We propose a novel framework leveraging generative 3D…

Graphics · Computer Science 2025-10-31 Zhiwei Zhao , Alan Zhao , Minchen Li , Yixin Hu

Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel framework consisting of two key components: (1) a strong…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Luxi Chen , Zihan Zhou , Min Zhao , Yikai Wang , Ge Zhang , Wenhao Huang , Hao Sun , Ji-Rong Wen , Chongxuan Li

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi

Despite recent progress, video diffusion models still struggle to synthesize realistic videos involving highly dynamic motions or requiring fine-grained motion controllability. A central limitation lies in the scarcity of such examples in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Wonjoon Jin , Jiyun Won , Janghyeok Han , Qi Dai , Chong Luo , Seung-Hwan Baek , Sunghyun Cho

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

Existing video generation models struggle to maintain long-term spatial and temporal consistency due to the dense, high-dimensional nature of video signals. To overcome this limitation, we propose Spatia, a spatial memory-aware video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Jinjing Zhao , Fangyun Wei , Zhening Liu , Hongyang Zhang , Chang Xu , Yan Lu

Maintaining spatial world consistency over long horizons remains a central challenge for camera-controllable video generation. Existing memory-based approaches often condition generation on globally reconstructed 3D scenes by rendering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Zun Wang , Han Lin , Jaehong Yoon , Jaemin Cho , Yue Zhang , Mohit Bansal

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

Dynamic Novel View Synthesis aims to generate photorealistic views of moving subjects from arbitrary viewpoints. This task is particularly challenging when relying on monocular video, where disentangling structure from motion is ill-posed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Michal Nazarczuk , Sibi Catley-Chandar , Thomas Tanay , Zhensong Zhang , Gregory Slabaugh , Eduardo Pérez-Pellitero

Novel view synthesis is a task of generating scenes from unseen perspectives; however, synthesizing dynamic scenes from blurry monocular videos remains an unresolved challenge that has yet to be effectively addressed. Existing novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Yeon-Ji Song , Jaein Kim , Byung-Ju Kim , Byoung-Tak Zhang

We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Zhening Huang , Hyeonho Jeong , Xuelin Chen , Yulia Gryaditskaya , Tuanfeng Y. Wang , Joan Lasenby , Chun-Hao Huang

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Junkai Yan , Yipeng Gao , Qize Yang , Xihan Wei , Xuansong Xie , Ancong Wu , Wei-Shi Zheng
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