Ford
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Map Query Efficiency | Ford 3 | Average Map Query Time (ns)41.18 | 20 | |
| Map Query Efficiency | ford 2 | Average Map Query Time (ns)45.85 | 17 | |
| Map Query Efficiency | ford 1 | Average Map Query Time (ns)45.13 | 17 | |
| Negative temporal attribution | FordA | Δŷc (2%)-0.1 | 14 | |
| Multivariate Time Series Classification | Ford | Accuracy78.05 | 10 | |
| LiDAR point cloud compression | Ford | BD-Rate D1-19.15 | 9 | |
| Occupancy Mapping | ford 3 | Map Accuracy99.98 | 8 | |
| Lossy Compression | Ford | BD-Rate-18.44 | 8 | |
| Point Cloud Compression | Ford (test) | bpp8.4 | 8 | |
| Occupancy Mapping | ford 2 | Map Accuracy99.99 | 7 | |
| Occupancy Mapping | ford 1 | Map Accuracy99.99 | 7 | |
| LiDAR Point Cloud Compression | Ford | Encoding Time (s)0.054 | 6 | |
| Compression Efficiency (BD-Rate) | Ford | BD-Rate D1-26.54 | 6 | |
| LiDAR Geometry Compression | Ford (test) | D1 Error (%)-26.54 | 6 | |
| Point Cloud Lossless Attribute Compression | Ford 02-03 | Bitrate (Bpp)4.52 | 6 | |
| Point Cloud Lossless Attribute Compression | Ford q1mm | Encoding Time (s/frame)0.9 | 3 | |
| Point Cloud Compression | Ford sequences 02 and 03 (eval) | BD-BR D1-82.54 | 3 |
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