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Referenced-based scene stylization that edits the appearance based on a content-aligned reference image is an emerging research area. Starting with a pretrained neural radiance field (NeRF), existing methods typically learn a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yiqun Mei , Jiacong Xu , Vishal M. Patel

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

Diffusion-based 2D virtual try-on (VTON) techniques have recently demonstrated strong performance, while the development of 3D VTON has largely lagged behind. Despite recent advances in text-guided 3D scene editing, integrating 2D VTON into…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Yukang Cao , Masoud Hadi , Liang Pan , Ziwei Liu

Recent advances in generative diffusion models have shown a notable inherent understanding of image style and semantics. In this paper, we leverage the self-attention features from pretrained diffusion networks to transfer the visual…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Yang Zhou , Xu Gao , Zichong Chen , Hui Huang

Abstract representations of 3D scenes play a crucial role in computer vision, enabling a wide range of applications such as mapping, localization, surface reconstruction, and even advanced tasks like SLAM and rendering. Among these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Chenggang Yang , Yuang Shi

Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-observed areas. Methods that leverage generative priors to correct artifacts in these areas…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Riccardo de Lutio , Tobias Fischer , Yen-Yu Chang , Yuxuan Zhang , Jay Zhangjie Wu , Xuanchi Ren , Tianchang Shen , Katarina Tothova , Zan Gojcic , Haithem Turki

Creating 4D fields of Gaussian Splatting from images or videos is a challenging task due to its under-constrained nature. While the optimization can draw photometric reference from the input videos or be regulated by generative models,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Quankai Gao , Qiangeng Xu , Zhe Cao , Ben Mildenhall , Wenchao Ma , Le Chen , Danhang Tang , Ulrich Neumann

3D Gaussian Splatting (3DGS) has emerged as a prominent paradigm for 3D reconstruction and novel view synthesis. However, it remains vulnerable to severe artifacts when trained under sparse-view constraints. While recent methods attempt to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Xiao Cao , Yuze Li , Youmin Zhang , Jiayu Song , Cheng Yan , Wen Li , Lixin Duan

Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility caused by scattering, attenuation, and sparse observations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

Recent advancements in large generative models and real-time neural rendering using point-based techniques pave the way for a future of widespread visual data distribution through sharing synthesized 3D assets. However, while standardized…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Chenxin Li , Hengyu Liu , Zhiwen Fan , Wuyang Li , Yifan Liu , Panwang Pan , Yixuan Yuan

Despite the impressive results of arbitrary image-guided style transfer methods, text-driven image stylization has recently been proposed for transferring a natural image into a stylized one according to textual descriptions of the target…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Nisha Huang , Yuxin Zhang , Fan Tang , Chongyang Ma , Haibin Huang , Yong Zhang , Weiming Dong , Changsheng Xu

We propose a novel 3D deepfake generation framework based on 3D Gaussian Splatting that enables realistic, identity-preserving face swapping and reenactment in a fully controllable 3D space. Compared to conventional 2D deepfake approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Wending Liu , Siyun Liang , Huy H. Nguyen , Isao Echizen

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull

Developing a unified pipeline that enables users to remove, re-texture, or replace objects in a versatile manner is crucial for text-guided 3D inpainting. However, there are still challenges in performing multiple 3D inpainting tasks within…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Jingyi Pan , Dan Xu , Qiong Luo

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

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

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

3D Gaussian Splatting (3DGS) has exhibited remarkable efficacy in novel view synthesis (NVS). However, it suffers from a significant drawback: achieving high-fidelity rendering typically necessitates a large number of 3D Gaussians,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Lintao Xiang , Xinkai Chen , Jianhuang Lai , Guangcong Wang

Neural style transfer (NST), where an input image is rendered in the style of another image, has been a topic of considerable progress in recent years. Research over that time has been dominated by transferring aspects of color and texture,…

Computer Vision and Pattern Recognition · Computer Science 2020-07-13 Xiao-Chang Liu , Xuan-Yi Li , Ming-Ming Cheng , Peter Hall

Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel view synthesis, parsing semantic labels, and tracking moving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hongyu Zhou , Jiahao Shao , Lu Xu , Dongfeng Bai , Weichao Qiu , Bingbing Liu , Yue Wang , Andreas Geiger , Yiyi Liao