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Building accurate maps is a key building block to enable reliable localization, planning, and navigation of autonomous vehicles. We propose a novel approach for building accurate maps of dynamic environments utilizing a sequence of LiDAR…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Xingguang Zhong , Yue Pan , Cyrill Stachniss , Jens Behley

Presenting a 3D scene from multiview images remains a core and long-standing challenge in computer vision and computer graphics. Two main requirements lie in rendering and reconstruction. Notably, SOTA rendering quality is usually achieved…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Mulin Yu , Tao Lu , Linning Xu , Lihan Jiang , Yuanbo Xiangli , Bo Dai

We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from monocular images. To achieve this, we leverage recent advances in dense monocular SLAM and real-time hierarchical…

Computer Vision and Pattern Recognition · Computer Science 2022-10-26 Antoni Rosinol , John J. Leonard , Luca Carlone

Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like object detection and semantic segmentation. Most prior works treat shadow detection and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zi-Yang Bo , Wei Lu , Hongruixuan Chen , Si-Bao Chen , Bin Luo

Existing methods for interactive segmentation in radiance fields entail scene-specific optimization and thus cannot generalize across different scenes, which greatly limits their applicability. In this work we make the first attempt at…

Computer Vision and Pattern Recognition · Computer Science 2023-08-10 Songlin Tang , Wenjie Pei , Xin Tao , Tanghui Jia , Guangming Lu , Yu-Wing Tai

We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single images from the Internet. Prior works on 3D-aware image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangzan Zhang , Sida Peng , Tianrun Chen , Linzhan Mou , Haotong Lin , Kaicheng Yu , Yiyi Liao , Xiaowei Zhou

Neural radiance fields enable novel-view synthesis and scene reconstruction with photorealistic quality from a few images, but require known and accurate camera poses. Conventional pose estimation algorithms fail on smooth or self-similar…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Axel Levy , Mark Matthews , Matan Sela , Gordon Wetzstein , Dmitry Lagun

Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow regions, resulting in severe artifacts around the shadow…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Lanqing Guo , Siyu Huang , Ding Liu , Hao Cheng , Bihan Wen

Implicit 3D surface reconstruction of an object from its partial and noisy 3D point cloud scan is the classical geometry processing and 3D computer vision problem. In the literature, various 3D shape representations have been developed,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Atharva Pandey , Vishal Yadav , Rajendra Nagar , Santanu Chaudhury

Neural radiance fields (NeRFs) have become a ubiquitous tool for modeling scene appearance and geometry from multiview imagery. Recent work has also begun to explore how to use additional supervision from lidar or depth sensor measurements…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Anagh Malik , Parsa Mirdehghan , Sotiris Nousias , Kiriakos N. Kutulakos , David B. Lindell

Satellite remote sensing missions have gained popularity over the past fifteen years due to their ability to cover large swaths of land at regular intervals, making them ideal for monitoring environmental trends. The FINCH mission, a 3U+…

Climate studies often rely on remotely sensed images to retrieve two-dimensional maps of cloud properties. To advance volumetric analysis, we focus on recovering the three-dimensional (3D) heterogeneous extinction coefficient field of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Tamar Klein , Tom Aizenberg , Roi Ronen

As we begin to consider modeling large, realistic 3D building scenes, it becomes necessary to consider a more compact representation over the polygonal mesh model. Due to the large amounts of annotated training data, which is costly to…

Computer Vision and Pattern Recognition · Computer Science 2019-01-18 Xia Li , Yen-Liang Lin , James Miller , Alex Cheon , Walt Dixon

We present a method to map 2D image observations of a scene to a persistent 3D scene representation, enabling novel view synthesis and disentangled representation of the movable and immovable components of the scene. Motivated by the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Prafull Sharma , Ayush Tewari , Yilun Du , Sergey Zakharov , Rares Ambrus , Adrien Gaidon , William T. Freeman , Fredo Durand , Joshua B. Tenenbaum , Vincent Sitzmann

In recent decades, the causes and consequences of climate change have accelerated, affecting our planet on an unprecedented scale. This change is closely tied to the ways in which humans alter their surroundings. As our actions continue to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Burak Ekim , Michael Schmitt

In recent years, analysis of remote sensing data has benefited immensely from borrowing techniques from the broader field of computer vision, such as the use of shared models pre-trained on large and diverse datasets. However, satellite…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Kartik Jindgar , Grace W. Lindsay

Shape from Polarization (SfP) estimates surface normals using photos captured at different polarizer rotations. Fundamentally, the SfP model assumes that light is reflected either diffusely or specularly. However, this model is not valid…

Computer Vision and Pattern Recognition · Computer Science 2016-06-14 Vage Taamazyan , Achuta Kadambi , Ramesh Raskar

Structured-light three-dimensional (3D) imaging can achieve 3D shape of a stationary object via one or more pixelated array cameras with phase-shifting illumination. In order to extend 3D imaging to moving scenarios, we propose a 3D imaging…

Image and Video Processing · Electrical Eng. & Systems 2019-05-01 Wen-Kai Yu

Accurate 3D reconstruction in visually-degraded underwater environments remains a formidable challenge. Single-modality approaches are insufficient: vision-based methods fail due to poor visibility and geometric constraints, while sonar is…

Robotics · Computer Science 2026-05-19 Lingpeng Chen , Jiakun Tang , Apple Pui-Yi Chui , Ziyang Hong , Junfeng Wu

We present a snapshot imaging technique for recovering 3D surrounding views of miniature scenes. Due to their intricacy, miniature scenes with objects sized in millimeters are difficult to reconstruct, yet miniatures are common in life and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yufan Zhang , Yu Ji , Yu Guo , Jinwei Ye