Symphony Lake Dataset (2016)

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.

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Full Laser Data (~7.1 GB)
Full Dowsampled Dataset (~24.6 GB)
One Year Sample (~199.4 MB)
Survey Parsing Code

Download per Survey:
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Survey Date
(YY-MM-DD)
Downsampled Dataset (5%) Full Dataset Laser Data Youtube Preview
160201 160201 (255M) 160201 (5.0G) 160201 (64M)

160211 160211 (214M) 160211 (4.2G) 160211 (54M)

160216 160216 (220M) 160216 (4.3G) 160216 (55M)

160305 160305 (217M) 160305 (4.3G) 160305 (58M)

160314 160314 (218M) 160314 (4.3G) 160314 (55M)

160321 160321 (190M) 160321 (3.8G) 160321 (59M)

160401 160401 (160M) 160401 (3.2G) 160401 (49M)

160407 160407 (189M) 160407 (4.1G) 160407 (58M)

160411 160411 (191M) 160411 (3.8G) 160411 (50M)

160418 160418 (192M) 160418 (3.8G) 160418 (50M)

160426 160426 (200M) 160426 (3.9G) 160426 (55M)

160502 160502 (191M) 160502 (3.8G) 160502 (47M)

160524 160524 (192M) 160524 (3.8G) 160524 (49M)

160601 160601 (173M) 160601 (3.4G) 160601 (52M)

160606 160606 (191M) 160606 (3.8G) 160606 (51M)

160616 160616 (187M) 160616 (3.7G) 160616 (52M)

160620 160620 (175M) 160620 (3.5G) 160620 (53M)

160715 160715 (189M) 160715 (3.7G) 160715 (53M)

160719 160719 (229M) 160719 (4.5G) 160719 (60M)

160725 160725 (186M) 160725 (3.7G) 160725 (67M)

160801 160801 (194M) 160801 (3.8G) 160801 (52M)

160808 160808 (195M) 160808 (3.9G) 160808 (55M)

160816 160816 (186M) 160816 (3.7G) 160816 (53M)

160821 160821 (158M) 160821 (3.1G) 160821 (52M)

160829 160829 (160M) 160829 (3.2G) 160829 (51M)

160906 160906 (146M) 160906 (2.9G) 160906 (47M)

160912 160912 (185M) 160912 (3.7G) 160912 (49M)

160923 160923 (182M) 160923 (3.6G) 160923 (50M)

160927 160927 (176M) 160927 (3.5G) 160927 (51M)

161003 161003 (172M) 161003 (3.4G) 161003 (50M)

161010 161010 (156M) 161010 (3.1G) 161010 (47M)

161018 161018 (169M) 161018 (3.4G) 161018 (47M)

161114 161114 (205M) 161114 (4.0G) 161114 (54M)

161123 161123 (220M) 161123 (4.3G) 161123 (51M)

161127 161127 (209M) 161127 (4.1G) 161127 (52M)

161216 161216 (223M) 161216 (4.4G) 161216 (58M)

161223 161223 (257M) 161223 (5.1G) 161223 (57M)

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References

Please cite the following paper if you use the dataset:

Relevant Papers: