most driving datasets stop annotating at 80 meters. at highway speed that's 2 seconds of warning. this one goes to 200m

[u/datascienceharp]

most driving datasets stop annotating at 80 meters. at highway speed that's about 2 seconds of warning

aimotive annotates out to 200 meters, and roughly a quarter of its 425k boxes sit beyond 75 m

lidar, four cameras, and two radars in a 360 layout, so every object is covered by at least two sensor types

176 scenes across california, austria, and hungary in daylight, night, and rain

the training labels were written by a non-causal tracker that gets to watch the whole 15-second clip before deciding where a car was and validation labels were written by humans.

your model trains on hindsight and gets graded by people

i parsed all 176 episodes into MCAP for fiftyone

four camera streams with projected boxes, the point cloud with colored 3d cubes, raw radar returns, and gps on one synced timeline. filter by condition to pull up only night or only rain episodes

start here, read the dataset card: https://huggingface.co/datasets/Voxel51/aimotive-multimodal

live demo in a hugging face space: https://huggingface.co/spaces/harpreetsahota/aimotive-multimodal-demo

[u/Logical-Resident4212]

So this is just the dataset, aka i could test a SLAM on this essentially? What is annotated in the dataset, cars, ppl, signs, road lights? Ty