Method: lcc-fastsam

User felix.stillger
Training image modalities RGB
Test image modalities RGB

Training: There is no training step.

Onboarding: For each object, 43 random pre-rendered images from the "train_pbr" dataset are selected. The masks of these objects are then extracted and encoded using CLIP. This data is input into a simple expert binary classifier, trained for each object.

Test: During testing, Fastsam-s extracts masks from a test image, and the object's ID is determined by the expert binary classifiers.

Computer specifications RTX 3090, AMD Ryzen 9 3900X 12-Core Processor

Public submissions

Date Submission name Dataset
2023-09-27 16:49 3rd stage TUD-L
2023-09-27 20:54 3rd. stage LM-O
2023-09-27 21:36 3rd. stage YCB-V
2023-09-27 21:39 3rd. stage T-LESS
2023-09-27 22:36 4th stage IC-BIN
2023-09-28 03:34 4th. stage ITODD
2023-09-28 04:38 4th stage HB