Method: ORSP-Net

User ISRI_SKKU
Publication
Implementation
Views Single
Test image modalities RGB-D
Description

Submitted to: BOP Challenge 2025

Training data: provided PBR + custom synthetic

Notes: Our cascaded YOLO–YOLACT framework integrates additional networks to maximize recall and improve precision. A Box Reorganization algorithm redefines precise RoIs, followed by an Image Classifier and Feature-Level Refinement to enhance class accuracy. Scene-Level Fusion combines class, score, and box information, yielding robust segmentation of small and heavily occluded objects.

Computer specifications CPU: Intel(R) Core(TM) i7-10700 CPU @ 2.90GHz; RAM: 64GB; GPU: NVIDIA TITAN X (Pascal)

Public submissions

Date Submission name Dataset
2025-10-01 15:27 ORSP-NET_Segm LM-O