TerraSky3D: Multi-View Reconstructions of European Landmarks in 4K
- URL: http://arxiv.org/abs/2603.28287v1
- Date: Mon, 30 Mar 2026 11:08:51 GMT
- Title: TerraSky3D: Multi-View Reconstructions of European Landmarks in 4K
- Abstract summary: Existing 3D datasets are either low resolution, limited to a small amount of scenes, based on images of varying quality because retrieved from the internet, or limited to specific capturing scenarios.<n>Motivated by this lack of suitable 3D datasets, we captured TerraSky3D, a high-resolution large-scale 3D reconstruction dataset comprising 50,000 images divided into 150 ground, aerial, and mixed scenes.
- Score: 12.214651317714939
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public datasets. Existing 3D datasets are either low resolution, limited to a small amount of scenes, based on images of varying quality because retrieved from the internet, or limited to specific capturing scenarios. Motivated by this lack of suitable 3D datasets, we captured TerraSky3D, a high-resolution large-scale 3D reconstruction dataset comprising 50,000 images divided into 150 ground, aerial, and mixed scenes. The dataset focuses on European landmarks and comes with curated calibration data, camera poses, and depth maps. TerraSky3D tries to answer the need for challenging dataset that can be used to train and evaluate 3D reconstruction-related pipelines.
Related papers
- Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond [27.57108346101154]
Holo360D is the first large-scale dataset that provides continuous panoramic sequences with accurately aligned depth maps.<n>To enhance the 3D data quality, a post-processing pipeline is proposed, including geometry denoising, mesh hole filling, and region-specific remeshing.<n>Results demonstrate that Holo360D delivers superior training signals and provides a comprehensive benchmark for advancing panoramic 3D reconstruction models.
arXiv Detail & Related papers (2026-04-24T12:03:27Z) - RS3DBench: A Comprehensive Benchmark for 3D Spatial Perception in Remote Sensing [71.75704516333394]
We present a visual Benchmark for 3D understanding of Remotely Sensed images, dubbed RS3DBench.<n>This dataset encompasses 54,951 pairs of remote sensing images and pixel-level aligned depth maps.<n>We introduce a remotely sensed depth estimation model derived from stable diffusion, harnessing its multimodal fusion capabilities.
arXiv Detail & Related papers (2025-09-23T11:20:51Z) - Towards Scalable Spatial Intelligence via 2D-to-3D Data Lifting [64.64738535860351]
We present a scalable pipeline that converts single-view images into comprehensive, scale- and appearance-realistic 3D representations.<n>Our method bridges the gap between the vast repository of imagery and the increasing demand for spatial scene understanding.<n>By automatically generating authentic, scale-aware 3D data from images, we significantly reduce data collection costs and open new avenues for advancing spatial intelligence.
arXiv Detail & Related papers (2025-07-24T14:53:26Z) - CULTURE3D: A Large-Scale and Diverse Dataset of Cultural Landmarks and Terrains for Gaussian-Based Scene Rendering [16.614203937535205]
Current state-of-the-art 3D reconstruction models face limitations in building extra-large scale outdoor scenes.<n>In this paper, we present a extra-large fine-grained dataset with 10 billion points composed of 41,006 drone-captured high-resolution aerial images.<n>Compared to existing datasets, ours offers significantly larger scale and higher detail, uniquely suited for fine-grained 3D applications.
arXiv Detail & Related papers (2025-01-12T20:36:39Z) - Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos [76.07894127235058]
We present a system for mining high-quality 4D reconstructions from internet stereoscopic, wide-angle videos.<n>We use this method to generate large-scale data in the form of world-consistent, pseudo-metric 3D point clouds.<n>We demonstrate the utility of this data by training a variant of DUSt3R to predict structure and 3D motion from real-world image pairs.
arXiv Detail & Related papers (2024-12-12T18:59:54Z) - Den-SOFT: Dense Space-Oriented Light Field DataseT for 6-DOF Immersive Experience [28.651514326042648]
We have built a custom mobile multi-camera large-space dense light field capture system.
Our aim is to contribute to the development of popular 3D scene reconstruction algorithms.
The collected dataset is much denser than existing datasets.
arXiv Detail & Related papers (2024-03-15T02:39:44Z) - Cross3DVG: Cross-Dataset 3D Visual Grounding on Different RGB-D Scans [6.936271803454143]
We present a novel task for cross-dataset visual grounding in 3D scenes (Cross3DVG)
We created RIORefer, a large-scale 3D visual grounding dataset.
It includes more than 63k diverse descriptions of 3D objects within 1,380 indoor RGB-D scans from 3RScan.
arXiv Detail & Related papers (2023-05-23T09:52:49Z) - 3D Data Augmentation for Driving Scenes on Camera [50.41413053812315]
We propose a 3D data augmentation approach termed Drive-3DAug, aiming at augmenting the driving scenes on camera in the 3D space.
We first utilize Neural Radiance Field (NeRF) to reconstruct the 3D models of background and foreground objects.
Then, augmented driving scenes can be obtained by placing the 3D objects with adapted location and orientation at the pre-defined valid region of backgrounds.
arXiv Detail & Related papers (2023-03-18T05:51:05Z) - MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices [78.20154723650333]
High-quality 3D ground-truth shapes are critical for 3D object reconstruction evaluation.
We introduce a novel multi-view RGBD dataset captured using a mobile device.
We obtain precise 3D ground-truth shape without relying on high-end 3D scanners.
arXiv Detail & Related papers (2023-03-03T14:02:50Z) - 3D reconstruction from spherical images: A review of techniques,
applications, and prospects [2.6432771146480283]
3D reconstruction plays an increasingly important role in modern photogrammetric systems.
With the rapid evolution and extensive use of professional and consumer-grade spherical cameras, spherical images show great potential for the 3D modeling of urban and indoor scenes.
This research provides a thorough survey of the state-of-the-art for 3D reconstruction of spherical images in terms of data acquisition, feature detection and matching, image orientation, and dense matching.
arXiv Detail & Related papers (2023-02-09T08:45:27Z) - Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments
for Embodied AI [55.475530452838946]
HM3D contains 112.5k m2 of space, which is 1.4 - 3.7x larger than other building-scale datasets such as MP3D and Gibson.
Images rendered from HM3D have 20 - 85% higher visual fidelity w.r.t. counterpart images captured with real cameras.
HM3D-trained PointNav agents achieve 100% performance on Gibson-test dataset.
arXiv Detail & Related papers (2021-09-16T22:01:24Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.