Some tasks are inferred based on the benchmarks list.
The benchmarks section lists all benchmarks using a given dataset or any of its variants. We use variants to distinguish between results evaluated on slightly different versions of the same dataset. For example, ImageNet 32⨉32 and ImageNet 64⨉64 are variants of the ImageNet dataset.
CrashD is a test benchmark for the robustness and generalization of 3D object detection models. It contains a wide range of out-of-distribution vehicles, including damaged, classic, and sports cars.