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Related papers: AI-Driven Stylization of 3D Environments

200 papers

Real-world human-built environments are highly dynamic, involving multiple humans and their complex interactions with surrounding objects. While 3D geometry modeling of such scenes is crucial for applications like AR/VR, gaming, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Sandika Biswas , Qianyi Wu , Biplab Banerjee , Hamid Rezatofighi

Current 3D stylization techniques primarily focus on static scenes, while our world is inherently dynamic, filled with moving objects and changing environments. Existing style transfer methods primarily target appearance -- such as color…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Nhat Phuong Anh Vu , Abhishek Saroha , Or Litany , Daniel Cremers

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

In computer graphics and vision, recovering easily modifiable scene appearance from image data is crucial for applications such as content creation. We introduce a novel method that integrates 3D Gaussian Splatting with an implicit surface…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Jakub Szymkowiak , Weronika Jakubowska , Dawid Malarz , Weronika Smolak-Dyżewska , Maciej Zięba , Przemyslaw Musialski , Wojtek Pałubicki , Przemysław Spurek

This project presents an exploration into 3D scene reconstruction of synthetic and real-world scenes using Neural Radiance Field (NeRF) approaches. We primarily take advantage of the reduction in training and rendering time of neural…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Benedict Quartey , Tuluhan Akbulut , Wasiwasi Mgonzo , Zheng Xin Yong

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

Generating photorealistic images with controllable camera pose and scene contents is essential for many applications including AR/VR and simulation. Despite the fact that rapid progress has been made in 3D-aware generative models, most…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Yuanbo Yang , Yifei Yang , Hanlei Guo , Rong Xiong , Yue Wang , Yiyi Liao

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

3D Gaussian Splatting (3DGS) has become the method of choice for photo-realistic 3D reconstruction of scenes, due to being able to efficiently and accurately recover the scene appearance and geometry from images. 3DGS represents the scene…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Ivan Desiatov , Torsten Sattler

Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussian Splatting (3DGS), where scenes are represented by a series…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Lanqing Guo , Yufei Wang , Hezhen Hu , Yan Zheng , Yeying Jin , Siyu Huang , Zhangyang Wang

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this constraint, multiple efforts have been made to train Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yang Fu , Sifei Liu , Amey Kulkarni , Jan Kautz , Alexei A. Efros , Xiaolong Wang

Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challenging, lacking a proper solution to achieve real-time,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yuxuan Yao , Zixuan Zeng , Chun Gu , Xiatian Zhu , Li Zhang

Although 3D Gaussian Splatting (3DGS) has achieved impressive performance in real-time rendering, its densification strategy often results in suboptimal reconstruction quality. In this work, we present a comprehensive improvement to the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Xiaobin Deng , Changyu Diao , Min Li , Ruohan Yu , Duanqing Xu

Dynamic reconstruction of deformable tissues in endoscopic video is a key technology for robot-assisted surgery. Recent reconstruction methods based on neural radiance fields (NeRFs) have achieved remarkable results in the reconstruction of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Weixing Xie , Junfeng Yao , Xianpeng Cao , Qiqin Lin , Zerui Tang , Xiao Dong , Xiaohu Guo

3D Gaussian Splatting (3DGS) is a recent approach for scene rendering. Although primarily designed for view synthesis, its potential for scene understanding tasks remains underexplored. In this work, we conduct a comparative evaluation of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Julia Farganus , Krzysztof Żurawicki , Arkadiusz Gaweł , Weronika Jakubowska , Halina Kwaśnicka

While NeRF-based 3D-aware image generation methods enable viewpoint control, limitations still remain to be adopted to various 3D applications. Due to their view-dependent and light-entangled volume representation, the 3D geometry presents…

Computer Vision and Pattern Recognition · Computer Science 2022-03-15 Minsoo Lee , Chaeyeon Chung , Hojun Cho , Minjung Kim , Sanghun Jung , Jaegul Choo , Minhyuk Sung

We present an efficient neural 3D scene representation for novel-view synthesis (NVS) in large-scale, dynamic urban areas. Existing works are not well suited for applications like mixed-reality or closed-loop simulation due to their limited…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Tobias Fischer , Jonas Kulhanek , Samuel Rota Bulò , Lorenzo Porzi , Marc Pollefeys , Peter Kontschieder

3D Gaussian Splatting has achieved remarkable success in reconstructing both static and dynamic 3D scenes. However, in a scene represented by 3D Gaussian primitives, interactions between objects suffer from inaccurate 3D segmentation,…

Graphics · Computer Science 2025-06-10 Zeyu Xiao , Zhenyi Wu , Mingyang Sun , Qipeng Yan , Yufan Guo , Zhuoer Liang , Lihua Zhang

While style transfer techniques have been well-developed for 2D image stylization, the extension of these methods to 3D scenes remains relatively unexplored. Existing approaches demonstrate proficiency in transferring colors and textures…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Dmytro Kotovenko , Olga Grebenkova , Nikolaos Sarafianos , Avinash Paliwal , Pingchuan Ma , Omid Poursaeed , Sreyas Mohan , Yuchen Fan , Yilei Li , Rakesh Ranjan , Björn Ommer

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang