Symphony Lake Dataset (2015)

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
150111 150111 (320M) 150111 (6.3G) 150111 (78M)

150216 150216 (274M) 150216 (5.4G) 150216 (68M)

150226 150226 (254M) 150226 (5.0G) 150226 (67M)

150305 150305 (237M) 150305 (4.7G) 150305 (63M)

150312 150312 (238M) 150312 (4.7G) 150312 (62M)

150320 150320 (225M) 150320 (4.4G) 150320 (59M)

150327 150327 (272M) 150327 (5.4G) 150327 (68M)

150401 150401 (161M) 150401 (3.2G) 150401 (31M)

150408 150408 (98M) 150408 (2.0G) 150408 (26M)

150414 150414 (268M) 150414 (5.3G) 150414 (73M)

150421 150421 (191M) 150421 (3.8G) 150421 (53M)

150429 150429 (212M) 150429 (4.2G) 150429 (60M)

150505 150505 (251M) 150505 (4.9G) 150505 (65M)

150522 150522 (221M) 150522 (4.4G) 150522 (60M)

150608 150608 (201M) 150608 (4.0G) 150608 (61M)

150620 150620 (196M) 150620 (3.9G) 150620 (57M)

150625 150625 (219M) 150625 (4.3G) 150625 (61M)

150701 150701 (273M) 150701 (5.4G) 150701 (78M)

150708 150708 (224M) 150708 (4.4G) 150708 (64M)

150723 150723 (204M) 150723 (4.0G) 150723 (57M)

150730 150730 (160M) 150730 (4.0G) 150730 (56M)

150806 150806 (206M) 150806 (4.1G) 150806 (56M)

150813 150813 (213M) 150813 (4.2G) 150813 (56M)

150820 150820 (187M) 150820 (3.7G) 150820 (51M)

150827 150827 (215M) 150827 (4.3G) 150827 (57M)

150902 150902 (98M) 150902 (2.0G) 150902 (28M)

150910 150910 (230M) 150910 (4.5G) 150910 (61M)

150918 150918 (169M) 150918 (3.3G) 150918 (52M)

150929 150929 (169M) 150929 (3.4G) 150929 (45M)

151008 151008 (171M) 151008 (3.4G) 151008 (53M)

151019 151019 (102M) 151019 (2.1G) 151019 (27M)

151027 151027 (191M) 151027 (3.8G) 151027 (51M)

151105 151105 (254M) 151105 (5.0G) 151105 (65M)

151111 151111 (177M) 151111 (3.5G) 151111 (50M)

151118 151118 (207M) 151118 (4.1G) 151118 (51M)

151127 151127 (190M) 151127 (3.7G) 151127 (59M)

151209 151209 (191M) 151209 (3.8G) 151209 (48M)

151214 151214 (229M) 151214 (4.5G) 151214 (59M)

151221 151221 (234M) 151221 (4.6G) 151221 (52M)

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References

Please cite the following paper if you use the dataset:

Relevant Papers: