Table 1.

ModelNet40 object classes selected and number of objects per class for the synthetic and real datasets.

Dataset	Bottle	Bowl	Chair	Cup	Keyboard	Lamp	Laptop	Monitor	Plant	Stool	${\mathit{N}}_{\mathit{Objects}}$
Training	335	64	889	79	145	124	149	465	240	90	2580
Augmentation.
Training	2680	512	7112	632	1160	992	1192	3720	1920	720	20,640
Sub.&Augmentation.
Training	816	448	1096	288	560	472	536	712	648	528	6104
Synthetic
Test	99	19	99	19	19	19	19	99	99	19	510
Camera
Test	64	48	64	64	48	48	48	48	48	48	528