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The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

Neural approaches have shown a significant progress on camera-based reconstruction. But they require either a fairly dense sampling of the viewing sphere, or pre-training on an existing dataset, thereby limiting their generalizability. In…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Mohammed Brahimi , Bjoern Haefner , Zhenzhang Ye , Bastian Goldluecke , Daniel Cremers

This paper presents a novel optimization-based method for non-line-of-sight (NLOS) imaging that aims to reconstruct hidden scenes under general setups with significantly reduced reconstruction time. In NLOS imaging, the visible surfaces of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Hyunbo Shim , In Cho , Daekyu Kwon , Seon Joo Kim

Gaussian Splatting (GS) enables immersive rendering, but realistic 3D object-scene composition remains challenging. Baked appearance and shadow information in GS radiance fields cause inconsistencies when combining objects and scenes.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Jian Gao , Mengqi Yuan , Yifei Zeng , Chang Zeng , Zhihao Li , Zhenyu Chen , Weichao Qiu , Xiao-Xiao Long , Hao Zhu , Xun Cao , Yao Yao

In the fields of photogrammetry, computer vision and computer graphics, the task of neural 3D scene reconstruction has led to the exploration of various techniques. Among these, 3D Gaussian Splatting stands out for its explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-05-06 Miriam Jäger , Theodor Kapler , Michael Feßenbecker , Felix Birkelbach , Markus Hillemann , Boris Jutzi

Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Honggyu An , Jaewoo Jung , Mungyeom Kim , Chaehyun Kim , Minkyeong Jeon , Jisang Han , Kazumi Fukuda , Takuya Narihira , Hyuna Ko , Junsu Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Jun-Kun Chen , Yu-Xiong Wang

Fringe projection profilometry-based 3-D reconstruction of objects with high reflectivity and low surface roughness remains a significant challenge. When measuring such glossy surfaces, specular reflection and indirect illumination often…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Sanghoon Jeon , Gihyun Jung , Suhyeon Ka , Jae-Sang Hyun

Semantic reconstruction of indoor scenes refers to both scene understanding and object reconstruction. Existing works either address one part of this problem or focus on independent objects. In this paper, we bridge the gap between…

Computer Vision and Pattern Recognition · Computer Science 2020-02-28 Yinyu Nie , Xiaoguang Han , Shihui Guo , Yujian Zheng , Jian Chang , Jian Jun Zhang

Capturing high-quality photographs under diverse real-world lighting conditions is challenging, as both natural lighting (e.g., low-light) and camera exposure settings (e.g., exposure time) significantly impact image quality. This challenge…

Computer Vision and Pattern Recognition · Computer Science 2025-04-24 Ziteng Cui , Xuangeng Chu , Tatsuya Harada

Full 3D estimation of human pose from a single image remains a challenging task despite many recent advances. In this paper, we explore the hypothesis that strong prior information about scene geometry can be used to improve pose estimation…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Zhe Wang , Liyan Chen , Shaurya Rathore , Daeyun Shin , Charless Fowlkes

We aim to recover the geometry of 3D parametric scenes using very few depth measurements from low-cost, commercially available time-of-flight sensors. These sensors offer very low spatial resolution (i.e., a single pixel), but image a wide…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Carter Sifferman , Yiquan Li , Yiming Li , Fangzhou Mu , Michael Gleicher , Mohit Gupta , Yin Li

We aim to tackle sparse-view reconstruction of a 360 3D scene using priors from latent diffusion models (LDM). The sparse-view setting is ill-posed and underconstrained, especially for scenes where the camera rotates 360 degrees around a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Soumava Paul , Christopher Wewer , Bernt Schiele , Jan Eric Lenssen

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world. Many existing methods solve this problem by optimizing a neural radiance field under the guidance of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Minghua Liu , Chao Xu , Haian Jin , Linghao Chen , Mukund Varma T , Zexiang Xu , Hao Su

Low-light 3D reconstruction from sparse views remains challenging due to exposure imbalance and degraded color fidelity. While existing methods struggle with view inconsistency and require per-scene training, we propose SplatBright, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yue Wen , Liang Song , Hesheng Wang

We present a new framework to reconstruct holistic 3D indoor scenes including both room background and indoor objects from single-view images. Existing methods can only produce 3D shapes of indoor objects with limited geometry quality…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Haolin Liu , Yujian Zheng , Guanying Chen , Shuguang Cui , Xiaoguang Han

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman

Conventional imaging only records photons directly sent from the object to the detector, while non-line-of-sight (NLOS) imaging takes the indirect light into account. Most NLOS solutions employ a transient scanning process, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2021-03-29 Dayu Zhu , Wenshan Cai