3D Car Instance Understanding
3 papers with code • 1 benchmarks • 2 datasets
3D Car Instance Understanding is the task of estimating properties (e.g.translation, rotation and shape) of a moving or parked vehicle on the road.
( Image credit: Occlusion-Net )
Benchmarks
These leaderboards are used to track progress in 3D Car Instance Understanding
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
ApolloCar3D
CarFusion
Latest papers with no code
Road traffic reservoir computing
Reservoir computing derived from recurrent neural networks is more applicable to real world systems than deep learning because of its low computational cost and potential for physical implementation.
ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving
Specifically, we first segment each car with a pre-trained Mask R-CNN, and then regress towards its 3D pose and shape based on a deformable 3D car model with or without using semantic keypoints.
