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In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource for perception tasks such as 3D object detection. Maps can provide robust structural priors of the static environment, helping resolve…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Yang Fu , Yuliang Zou , Hao Xiang , Xin Huang , Yijing Bai , Chen Song , Weijing Shi , Govind Thattai , Dragomir Anguelov , Mingxing Tan , Yingwei Li

Learning surfaces from neural radiance field (NeRF) became a rising topic in Multi-View Stereo (MVS). Recent Signed Distance Function (SDF)-based methods demonstrated their ability to reconstruct accurate 3D shapes of Lambertian scenes.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 LI Yang , WU Ruizheng , LI Jiyong , CHEN Ying-cong

With the recent advances in autonomous driving and the decreasing cost of LiDARs, the use of multimodal sensor systems is on the rise. However, in order to make use of the information provided by a variety of complimentary sensors, it is…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Quentin Herau , Nathan Piasco , Moussab Bennehar , Luis Roldão , Dzmitry Tsishkou , Cyrille Migniot , Pascal Vasseur , Cédric Demonceaux

Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model is almost impossible. In this paper, we propose a method capable of…

Computer Vision and Pattern Recognition · Computer Science 2014-06-20 Vikas Reddy , Conrad Sanderson , Andres Sanin , Brian C. Lovell

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

Neural Radiance Fields (NeRF) can be optimized to obtain high-fidelity 3D scene reconstructions of objects and large-scale scenes. However, NeRFs require accurate camera parameters as input -- inaccurate camera parameters result in blurry…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Keunhong Park , Philipp Henzler , Ben Mildenhall , Jonathan T. Barron , Ricardo Martin-Brualla

This paper presents a novel approach to underwater terrain mapping for Autonomous Underwater Vehicles (AUVs) operating in close proximity to complex 3D environments. The proposed methodology creates a probabilistic elevation map of the…

Robotics · Computer Science 2020-03-24 Bilal Arain , Feras Dayoub , Paul Rigby , Matthew Dunbabin

Robust GNSS positioning in urban environments is still plagued by multipath effects, particularly due to the complex signal propagation induced by ubiquitous surfaces with varied radio frequency reflectivities. Current 3D Mapping Aided…

Signal Processing · Electrical Eng. & Systems 2025-04-24 Shiyao Lv , Xin Zhang , Xingqun Zhan

Existing depth sensors are imperfect and may provide inaccurate depth values in challenging scenarios, such as in the presence of transparent or reflective objects. In this work, we present a general framework that leverages polarization…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Kei Ikemura , Yiming Huang , Felix Heide , Zhaoxiang Zhang , Qifeng Chen , Chenyang Lei

Helmholtz stereopsis is one the versatile techniques for 3D geometry reconstruction from 2D images of objects with unknown and arbitrary reflectance surfaces. HS eliminates the need for surface reflectance, a challenging parameter to…

Image and Video Processing · Electrical Eng. & Systems 2024-07-29 Razieh Azizi , Hamidreza Amindavar , Hassan Aghaeinia

Safe motion planning in robotics requires planning into space which has been verified to be free of obstacles. However, obtaining such environment representations using lidars is challenging by virtue of the sparsity of their depth…

Current methods for 3D reconstruction and environmental mapping frequently face challenges in achieving high precision, highlighting the need for practical and effective solutions. In response to this issue, our study introduces FlyNeRF, a…

Robotics · Computer Science 2024-04-22 Maria Dronova , Vladislav Cheremnykh , Alexey Kotcov , Aleksey Fedoseev , Dzmitry Tsetserukou

We propose SDFDiff, a novel approach for image-based shape optimization using differentiable rendering of 3D shapes represented by signed distance functions (SDFs). Compared to other representations, SDFs have the advantage that they can…

Computer Vision and Pattern Recognition · Computer Science 2022-02-23 Yue Jiang , Dantong Ji , Zhizhong Han , Matthias Zwicker

We are witnessing an explosion of neural implicit representations in computer vision and graphics. Their applicability has recently expanded beyond tasks such as shape generation and image-based rendering to the fundamental problem of…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Jiaming Sun , Xi Chen , Qianqian Wang , Zhengqi Li , Hadar Averbuch-Elor , Xiaowei Zhou , Noah Snavely

Self-supervised methods have showed promising results on depth estimation task. However, previous methods estimate the target depth map and camera ego-motion simultaneously, underusing multi-frame correlation information and ignoring the…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Songchun Zhang , Chunhui Zhao

This study explores the use of photometric techniques (shape-from-shading and uncalibrated photometric stereo) for upsampling the low-resolution depth map from an RGB-D sensor to the higher resolution of the companion RGB image. A…

Computer Vision and Pattern Recognition · Computer Science 2019-06-26 Bjoern Haefner , Songyou Peng , Alok Verma , Yvain Quéau , Daniel Cremers

We present a method for transferring the artistic features of an arbitrary style image to a 3D scene. Previous methods that perform 3D stylization on point clouds or meshes are sensitive to geometric reconstruction errors for complex…

Computer Vision and Pattern Recognition · Computer Science 2022-06-14 Kai Zhang , Nick Kolkin , Sai Bi , Fujun Luan , Zexiang Xu , Eli Shechtman , Noah Snavely

Recent advances in mapping techniques have enabled the creation of highly accurate dense 3D maps during robotic missions, such as point clouds, meshes, or NeRF-based representations. These developments present new opportunities for reusing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Lintong Zhang , Yifu Tao , Jiarong Lin , Fu Zhang , Maurice Fallon

Digital artists often improve the aesthetic quality of digital photographs through manual retouching. Beyond global adjustments, professional image editing programs provide local adjustment tools operating on specific parts of an image.…

Computer Vision and Pattern Recognition · Computer Science 2020-04-01 Sean Moran , Pierre Marza , Steven McDonagh , Sarah Parisot , Gregory Slabaugh

A depth map can be represented by a set of learned bases and can be efficiently solved in a closed form solution. However, one issue with this method is that it may create artifacts when colour boundaries are inconsistent with depth…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Yiran Zhong , Yuchao Dai , Hongdong Li
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