# 4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving

arXiv: https://arxiv.org/abs/2009.06364 · HTML: https://mlsanity.com/paper/2009.06364/

## Key facts

- Cited by 51 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Sep 2020.

## Built on by (most cited first, 30 of 51)

- [LaMAR: Benchmarking Localization and Mapping for Augmented Reality](https://mlsanity.com/paper/2210.10770/) (2022)
- [Deep Patch Visual SLAM](https://mlsanity.com/paper/2408.01654/) (2024)
- [A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook](https://mlsanity.com/paper/2401.01454/) (2024)
- [DM-VIO: Delayed Marginalization Visual-Inertial Odometry](https://mlsanity.com/paper/2201.04114/) (2022)
- [Open-sourced Data Ecosystem in Autonomous Driving: the Present and Future](https://mlsanity.com/paper/2312.03408/) (2023)
- [ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception](https://mlsanity.com/paper/2104.13395/) (2021)
- [RobustLoc: Robust Camera Pose Regression in Challenging Driving Environments](https://mlsanity.com/paper/2211.11238/) (2022)
- [A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services](https://mlsanity.com/paper/2304.14271/) (2023)
- [GigaSLAM: Large-Scale Monocular SLAM with Hierarchical Gaussian Splats](https://mlsanity.com/paper/2503.08071/) (2025)
- [Benchmarking Egocentric Visual-Inertial SLAM at City Scale](https://mlsanity.com/paper/2509.26639/) (2025)
- [Active Visual Exploration Based on Attention-Map Entropy](https://mlsanity.com/paper/2303.06457/) (2023)
- [Asynchronous Multi-View SLAM](https://mlsanity.com/paper/2101.06562/) (2021)
- [Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning](https://mlsanity.com/paper/2403.11460/) (2024)
- [Ad-datasets: a meta-collection of data sets for autonomous driving](https://mlsanity.com/paper/2202.01909/) (2022)
- [MegLoc: A Robust and Accurate Visual Localization Pipeline](https://mlsanity.com/paper/2111.13063/) (2021)
- [VGGT-Motion: Motion-Aware Calibration-Free Monocular SLAM for Long-Range Consistency](https://mlsanity.com/paper/2602.05508/) (2026)
- [Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments](https://mlsanity.com/paper/2403.13395/) (2024)
- [AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale](https://mlsanity.com/paper/2404.03482/) (2024)
- [Privacy-Preserving Visual Localization with Event Cameras](https://mlsanity.com/paper/2212.03177/) (2022)
- [4Seasons: Benchmarking Visual SLAM and Long-Term Localization for Autonomous Driving in Challenging Conditions](https://mlsanity.com/paper/2301.01147/) (2022)
- [AdaSfM: From Coarse Global to Fine Incremental Adaptive Structure from Motion](https://mlsanity.com/paper/2301.12135/) (2023)
- [Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry](https://mlsanity.com/paper/2102.01191/) (2021)
- [Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications](https://mlsanity.com/paper/2203.01087/) (2022)
- [Unsupervised Quality Prediction for Improved Single-Frame and Weighted Sequential Visual Place Recognition](https://mlsanity.com/paper/2307.01464/) (2023)
- [Light-SLAM: A Robust Deep-Learning Visual SLAM System Based on LightGlue under Challenging Lighting Conditions](https://mlsanity.com/paper/2407.02382/) (2024)
- [ROVER: A Multi-Season Dataset for Visual SLAM](https://mlsanity.com/paper/2412.02506/) (2024)
- [ImPosing: Implicit Pose Encoding for Efficient Visual Localization](https://mlsanity.com/paper/2205.02638/) (2022)
- [RoMeO: Robust Metric Visual Odometry](https://mlsanity.com/paper/2412.11530/) (2024)
- [Spatially Visual Perception for End-to-End Robotic Learning](https://mlsanity.com/paper/2411.17458/) (2024)
- [ConDo: Continual Domain Expansion for Absolute Pose Regression](https://mlsanity.com/paper/2412.13452/) (2024)

## Abstract (arXiv)

We present a novel dataset covering seasonal and challenging perceptual conditions for autonomous driving. Among others, it enables research on visual odometry, global place recognition, and map-based re-localization tracking. The data was collected in different scenarios and under a wide variety of weather conditions and illuminations, including day and night. This resulted in more than 350 km of recordings in nine different environments ranging from multi-level parking garage over urban (including tunnels) to countryside and highway. We provide globally consistent reference poses with up-to centimeter accuracy obtained from the fusion of direct stereo visual-inertial odometry with RTK-GNSS. The full dataset is available at https://go.vision.in.tum.de/4seasons.