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In this paper, we present a novel deep method to reconstruct a point cloud of an object from a single still image. Prior arts in the field struggle to reconstruct an accurate and scalable 3D model due to either the inefficient and expensive…

Computer Vision and Pattern Recognition · Computer Science 2019-11-18 Anh-Duc Nguyen , Seonghwa Choi , Woojae Kim , Sanghoon Lee

Grazing Incidence X-ray Diffraction (GIXD) is a surface sensitive X-ray investigation technique (or geometry configuration) that can reveal the structural properties of a film deposited on a flat substrate. The term grazing indicates that…

Soft Condensed Matter · Physics 2015-12-29 Samuele Lilliu , Thomas Dane

Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations. Existing dynamic scene reconstruction methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiahui Li , Shengeng Tang , Jingxuan He , Gang Huang , Zhangye Wang , Yantao Pan , Lechao Cheng

Recently, reconstructing scenes from a single panoramic image using advanced 3D Gaussian Splatting (3DGS) techniques has attracted growing interest. Panoramic images offer a 360$\times$ 180 field of view (FoV), capturing the entire scene in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Zhijie Shen , Chunyu Lin , Shujuan Huang , Lang Nie , Kang Liao , Yao Zhao

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

Existing 4D Gaussian Splatting (4DGS) methods struggle to accurately reconstruct dynamic scenes, often failing to resolve ambiguous pixel correspondences and inadequate densification in dynamic regions. We address these issues by…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Taeho Kang , Jaeyeon Park , Kyungjin Lee , Youngki Lee

This paper provides a comprehensive survey on pioneer and state-of-the-art 3D scene geometry estimation methodologies based on single, two, or multiple images captured under the omnidirectional optics. We first revisit the basic concepts of…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Thiago Lopes Trugillo da Silveira , Paulo Gamarra Lessa Pinto , Jeffri Erwin Murrugarra Llerena , Claudio Rosito Jung

While 2D generative adversarial networks have enabled high-resolution image synthesis, they largely lack an understanding of the 3D world and the image formation process. Thus, they do not provide precise control over camera viewpoint or…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Katja Schwarz , Yiyi Liao , Michael Niemeyer , Andreas Geiger

Scene-consistent video generation aims to create videos that explore 3D scenes based on a camera trajectory. Previous methods rely on video generation models with external memory for consistency, or iterative 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 JiaKui Hu , Jialun Liu , Liying Yang , Xinliang Zhang , Kaiwen Li , Shuang Zeng , Yuanwei Li , Haibin Huang , Chi Zhang , Yanye Lu

Recent advancements in camera-based occupancy prediction have focused on the simultaneous prediction of 3D semantics and scene flow, a task that presents significant challenges due to specific difficulties, e.g., occlusions and unbalanced…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Ziyue Zhu , Shenlong Wang , Jin Xie , Jiang-jiang Liu , Jingdong Wang , Jian Yang

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

We propose an image synthesis approach that provides stratified navigation in the latent code space. With a tiny amount of partial or very low-resolution image, our approach can consistently out-perform state-of-the-art counterparts in…

Computer Vision and Pattern Recognition · Computer Science 2020-06-04 Lingzhi Zhang , Jiancong Wang , Yinshuang Xu , Jie Min , Tarmily Wen , James C. Gee , Jianbo Shi

Surface reconstruction and novel view rendering from sparse-view images are challenging. Signed Distance Function (SDF)-based methods struggle with fine details, while 3D Gaussian Splatting (3DGS)-based approaches lack global geometry…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Zihui Gao , Jia-Wang Bian , Guosheng Lin , Hao Chen , Chunhua Shen

We propose a new framework to systematically incorporate data uncertainty in Gaussian Splatting. Being the new paradigm of neural rendering, Gaussian Splatting has been investigated in many applications, with the main effort in extending…

Graphics · Computer Science 2026-04-28 Doğa Yılmaz , Jialin Zhu , Deshan Gong , He Wang

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

This paper presents a multimodal framework that integrates touch signals (contact points and surface normals) into 3D Gaussian Splatting (3DGS). Our approach enhances scene reconstruction, particularly under challenging conditions like low…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Yuchen Gao , Xiao Xu , Eckehard Steinbach , Daniel E. Lucani , Qi Zhang

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin