We lifted 10 functions out of this paper's own repositories and ran 8 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| mttgdd/oord-dataset | pwc_unofficial | 8 of 10 |
| Function | Status | Where it lives |
|---|---|---|
| do_cluster | Ran | mttgdd/oord-dataset/src/radvlad.py code served (permissive licence) · get_code("0eb4824d1e814184") |
| get_cfg_impl | Ran | mttgdd/oord-dataset/config/config.py code served (permissive licence) · get_code("c461d090c8f01e4a") |
| get_data_yaml | Ran | mttgdd/oord-dataset/config/config.py code served (permissive licence) · get_code("303a2cf55635c776") |
| get_distances | Ran | mttgdd/oord-dataset/src/compute_distance_matrix.py code served (permissive licence) · get_code("2aa1c8370d9d7f81") |
| get_embeddings | Ran | mttgdd/oord-dataset/src/compute_distance_matrix.py code served (permissive licence) · get_code("adbf95aba4ffd8f5") |
| get_gps_yaml | Ran | mttgdd/oord-dataset/config/config.py code served (permissive licence) · get_code("2d7c6779a9ea3e5a") |
| load_radar | Ran | mttgdd/oord-dataset/src/radar.py code served (permissive licence) · get_code("b14f4994eab7f2ce") |
| radar_polar_to_cartesian | Ran | mttgdd/oord-dataset/src/radar.py code served (permissive licence) · get_code("0cb1d09d7f2202d8") |
| get_nn | Not yet run | mttgdd/oord-dataset/src/models.py code served (permissive licence) · get_code("5fd5cfa5f74a1297") |
| get_vlad | Not yet run | mttgdd/oord-dataset/src/radvlad.py code served (permissive licence) · get_code("abdd13a84a45b04f") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
In this paper we present The Oxford Radar RobotCar Dataset, a new dataset for researching scene understanding using Millimetre-Wave FMCW scanning radar data. The target application is autonomous vehicles where this modality is robust to environmental conditions such as fog, rain, snow, or lens flare, which typically challenge other sensor modalities such as vision and LIDAR. The data were gathered in January 2019 over thirty-two traversals of a central Oxford route spanning a total of 280km of urban driving. It encompasses a variety of weather, traffic, and lighting conditions. This 4.7TB dataset consists of over 240,000 scans from a Navtech CTS350-X radar and 2.4 million scans from two Velodyne HDL-32E 3D LIDARs; along with six cameras, two 2D LIDARs, and a GPS/INS receiver. In addition we release ground truth optimised radar odometry to provide an additional impetus to research in this domain. The full dataset is available for download at: ori.ox.ac.uk/datasets/radar-robotcar-dataset
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1909.01300")
get_code_for_paper("1909.01300")
have("1909.01300")
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