Home
Datasets
Vaihingen-CR

Vaihingen-CR

Get this data View sample

Paper This dataset is released as part of our ECCV 2026 paper: Interpretation-Oriented Cloud Removal via Observation-Anchored Residual Flow with Geo-Contextual Alignment Paper page: arXiv: Code:

Source: Hugging Face Hub (wzy6055/vaihingen-cr). Metadata imported from the dataset’s Hub tags.

Dataset details

Tasks: Depth Estimation Image Segmentation Image-to-Image
License: MIT
Size: 1K–10K
Format: Text (raw)
Domain: Geospatial & Earth Observation
Hosted on: Hugging Face
Released: 2026-07
Access: Open
Downloads: 5.1K
Paper: Read paper

Get this data

Related datasets

Featured

Multimodal Sensor / Time-series Video

Open X-Embodiment

1M+ real-robot trajectories from 20+ institutions.

1M–10M·Apache-2.0·rosbag

Featured

Multimodal Video

Ego4D

3,670 hours of first-person video across hundreds of scenarios.

1M–10M·Custom / Research-only·Video (mp4)

Featured

Image LiDAR / Radar Multimodal

nuScenes

1,000 driving scenes with 360° camera, LiDAR and radar.

100K–1M·CC-BY-NC·Point Cloud (LAS/PLY)

Multimodal Tabular Text

Largest Logistics Companies

<1K·CC0·Parquet

From the blog

August 17, 2026 · Synthetic Data

Avoiding Data Leakage in Synthetic Data Projects

Synthetic data offers vast opportunities for machine learning model training without real-world constraints. Yet, beneath this promise lies the risk of…

August 17, 2026 · Synthetic Data

Practical Guide to Scaling Synthetic Data Solutions

Imagine handling a growing machine learning project with increasing demands for training data. Traditional data methods can't keep up, making synthetic…

August 17, 2026 · Synthetic Data

Mastering Synthetic Data Generation: From Concepts to Deployment

Synthetic data is more than a trend; it's a crucial tool for building strong AI models, especially when real-world data is scarce, sensitive, or…

Vaihingen-CR

Archives

Categories