Symphony Lake Dataset consists of 121 visual surveys of a lakeshore over more than three years in Metz, France. Unique from roadway datasets, it adds breadth to a space at a time when larger and more diverse datasets are needed to train data hungry machine learning methods. Over 5 million images from an unmanned surface vehicle capture the unstructured, natural environment as it evolved over time. Significant variation in appearance is present on time scales of weeks, seasons, and years. Success in this space may demonstrate advancements in perception, SLAM, and environment monitoring.
The complete raw surveys can be found on the following links:
On top of the raw surveys, some pre-processed results are also available:
Symphony Lake Dataset Visual Benchmark
Symphony Lake Dataset image pair dataset
© 2019 – 2023 DREAM Lab – Georgia Tech