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Articulated object reconstruction from sparse-view images is an ill-posed problem that requires simultaneous inference of geometry and underlying articulation structure. Existing methods for articulated object reconstruction based on NeRF…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Inseo Lee , Yoonji Kim , Eugene Sohn , Jiwoong Lee , Jungmin You , Joonseok Lee , Jin-Hwa Kim

The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple single-view image. However, due to the partial priors provided by single-view input, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Tianyi Gong , Boyan Li , Yifei Zhong , Fangxin Wang

We introduce AnySplat, a feed forward network for novel view synthesis from uncalibrated image collections. In contrast to traditional neural rendering pipelines that demand known camera poses and per scene optimization, or recent feed…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Lihan Jiang , Yucheng Mao , Linning Xu , Tao Lu , Kerui Ren , Yichen Jin , Xudong Xu , Mulin Yu , Jiangmiao Pang , Feng Zhao , Dahua Lin , Bo Dai

We aim to address sparse-view reconstruction of a 3D scene by leveraging priors from large-scale vision models. While recent advancements such as 3D Gaussian Splatting (3DGS) have demonstrated remarkable successes in 3D reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Hanyang Yu , Xiaoxiao Long , Ping Tan

In-the-wild photo collections often contain limited volumes of imagery and exhibit multiple appearances, e.g., taken at different times of day or seasons, posing significant challenges to scene reconstruction and novel view synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Deming Li , Kaiwen Jiang , Yutao Tang , Ravi Ramamoorthi , Rama Chellappa , Cheng Peng

As XR technology continues to advance rapidly, 3D generation and editing are increasingly crucial. Among these, stylization plays a key role in enhancing the appearance of 3D models. By utilizing stylization, users can achieve consistent…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Dingxi Zhang , Yu-Jie Yuan , Zhuoxun Chen , Fang-Lue Zhang , Zhenliang He , Shiguang Shan , Lin Gao

Feed-forward 3D Gaussian splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Although omnidirectional images are becoming more popular since…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Suyoung Lee , Jaeyoung Chung , Kihoon Kim , Jaeyoo Huh , Gunhee Lee , Minsoo Lee , Kyoung Mu Lee

We address the task of multi-view image editing from sparse input views, where the inputs can be seen as a mix of images capturing the scene from different viewpoints. The goal is to modify the scene according to a textual instruction while…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Daniel Gilo , Or Litany

3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purpose and not tailored to the structure of the problem. In…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Naama Pearl , Stefano Esposito , Haofei Xu , Amit Peleg , Patricia Gschossmann , Lorenzo Porzi , Peter Kontschieder , Gerard Pons-Moll , Andreas Geiger

This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection…

Graphics · Computer Science 2025-10-01 Zhenyu Shu , Junlong Yu , Kai Chao , Shiqing Xin , Ligang Liu

Standard 3D Gaussian Splatting (3DGS) relies on known or pre-computed camera poses and a sparse point cloud, obtained from structure-from-motion (SfM) preprocessing, to initialize and grow 3D Gaussians. We propose a novel SfM-Free 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Bo Ji , Angela Yao

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

Personalizing 3D scenes from a single reference image enables intuitive user-guided editing, which requires achieving both multi-view consistency across perspectives and referential consistency with the input image. However, these goals are…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Yuxuan Wang , Xuanyu Yi , Qingshan Xu , Yuan Zhou , Long Chen , Hanwang Zhang

Reconstructing 3D scenes from multiple viewpoints is a fundamental task in stereo vision. Recently, advances in generalizable 3D Gaussian Splatting have enabled high-quality novel view synthesis for unseen scenes from sparse input views by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Shengji Tang , Weicai Ye , Peng Ye , Weihao Lin , Yang Zhou , Tao Chen , Wanli Ouyang

Despite significant strides in the field of 3D scene editing, current methods encounter substantial challenge, particularly in preserving 3D consistency in multi-view editing process. To tackle this challenge, we propose a progressive 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Chaofan Luo , Donglin Di , Xun Yang , Yongjia Ma , Zhou Xue , Chen Wei , Yebin Liu

In this paper, we aim ambitiously for a realistic yet challenging problem, namely, how to reconstruct high-quality 3D scenes from sparse low-resolution views that simultaneously suffer from deficient perspectives and clarity. Whereas…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Yecong Wan , Mingwen Shao , Yuanshuo Cheng , Wangmeng Zuo

Prevailing 2D-centric visuomotor policies exhibit a pronounced deficiency in novel view generalization, as their reliance on static observations hinders consistent action mapping across unseen views. In response, we introduce GenSplat, a…

Robotics · Computer Science 2026-04-01 Sen Wang , Huaiyi Dong , Jingyi Tian , Jiayi Li , Zhuo Yang , Tongtong Cao , Anlin Chen , Shuang Wu , Le Wang , Sanping Zhou

3D Gaussian Splatting (3DGS) has enabled efficient 3D scene reconstruction from everyday images with real-time, high-fidelity rendering, greatly advancing VR/AR applications. Fisheye cameras, with their wider field of view (FOV), promise…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Zhengxian Yang , Fei Xie , Xutao Xue , Rui Zhang , Taicheng Huang , Yang Liu , Mengqi Ji , Tao Yu

We present Edit3r, a feed-forward framework that reconstructs and edits 3D scenes in a single pass from unposed, view-inconsistent, instruction-edited images. Unlike prior methods requiring per-scene optimization, Edit3r directly predicts…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Jiageng Liu , Weijie Lyu , Xueting Li , Yejie Guo , Ming-Hsuan Yang

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an assumption that is often violated in real-world applications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhankuo Xu , Chaoran Feng , Yingtao Li , Jianbin Zhao , Jiashu Yang , Wangbo Yu , Li Yuan , Yonghong Tian
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