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Related papers: SceneWiz3D: Towards Text-guided 3D Scene Compositi…

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Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiacheng Chen , Ramin Mehran , Xuhui Jia , Saining Xie , Sanghyun Woo

Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks. This work proposes a method to incrementally build up semantic scene graphs from a 3D environment given a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Shun-Cheng Wu , Johanna Wald , Keisuke Tateno , Nassir Navab , Federico Tombari

Text-to-3D generation has achieved remarkable success via large-scale text-to-image diffusion models. Nevertheless, there is no paradigm for scaling up the methodology to urban scale. Urban scenes, characterized by numerous elements,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Fan Lu , Kwan-Yee Lin , Yan Xu , Hongsheng Li , Guang Chen , Changjun Jiang

Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from significant view changes and scene scale. Previous efforts mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zuoyue Li , Zhenqiang Li , Zhaopeng Cui , Marc Pollefeys , Martin R. Oswald

In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable of producing high-fidelity shapes with colors that match the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhengzhe Liu , Yi Wang , Xiaojuan Qi , Chi-Wing Fu

Accurately reconstructing complex full multi-object scenes from sparse observations remains a core challenge in computer vision and a key step toward scalable and reliable simulation for robotics. In this work, we introduce RecGen, a…

Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou

Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling static editing and dynamic generation, while also struggling…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Ruisi Zhao , Zechuan Zhang , Zongxin Yang , Yi Yang

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical vision features, thus inevitably falling prey to the problem…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Yu Zhao , Hao Fei , Wei Ji , Jianguo Wei , Meishan Zhang , Min Zhang , Tat-Seng Chua

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

Creating large-scale virtual urban scenes with variant styles is inherently challenging. To facilitate prototypes of virtual production and bypass the need for complex materials and lighting setups, we introduce the first…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Yingshu Chen , Huajian Huang , Tuan-Anh Vu , Ka Chun Shum , Sai-Kit Yeung

We introduce SceneDiffuser, a conditional generative model for 3D scene understanding. SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization, and planning. In contrast to prior works, SceneDiffuser is…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Siyuan Huang , Zan Wang , Puhao Li , Baoxiong Jia , Tengyu Liu , Yixin Zhu , Wei Liang , Song-Chun Zhu

Despite advances in text-to-3D generation methods, generation of multi-object arrangements remains challenging. Current methods exhibit failures in generating physically plausible arrangements that respect the provided text description. We…

Graphics · Computer Science 2025-06-04 Hou In Ivan Tam , Hou In Derek Pun , Austin T. Wang , Angel X. Chang , Manolis Savva

We combine neural rendering with multi-modal image and text representations to synthesize diverse 3D objects solely from natural language descriptions. Our method, Dream Fields, can generate the geometry and color of a wide range of objects…

Computer Vision and Pattern Recognition · Computer Science 2022-05-05 Ajay Jain , Ben Mildenhall , Jonathan T. Barron , Pieter Abbeel , Ben Poole

Despite recent advances in text-conditioned 3D indoor scene generation, there remain gaps in the evaluation of these methods. Existing metrics often measure realism by comparing generated scenes to a set of ground-truth scenes, but they…

Graphics · Computer Science 2026-03-10 Hou In Ivan Tam , Hou In Derek Pun , Austin T. Wang , Angel X. Chang , Manolis Savva

Generative models have gained significant attention in novel view synthesis (NVS) by alleviating the reliance on dense multi-view captures. However, existing methods typically fall into a conventional paradigm, where generative models first…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Weiliang Chen , Jiayi Bi , Yuanhui Huang , Wenzhao Zheng , Yueqi Duan

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

We present a novel video generation framework that integrates 3-dimensional geometry and dynamic awareness. To achieve this, we augment 2D videos with 3D point trajectories and align them in pixel space. The resulting 3D-aware video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Yunuo Chen , Junli Cao , Vidit Goel , Sergei Korolev , Chenfanfu Jiang , Jian Ren , Sergey Tulyakov , Anil Kag
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