Submission: PoseDETR/LM-O/PBR-RGB

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Submission name PBR-RGB
Submission time (UTC) Jan. 13, 2026, 8:14 a.m.
User sthimm
Task Model-based 6D localization of seen objects
Dataset LM-O
Description
Evaluation scores
AR:0.695
AR_MSPD:0.847
AR_MSSD:0.695
AR_VSD:0.543
average_time_per_image:0.012

Method: PoseDETR

User sthimm
Publication
Implementation
Training image modalities RGB
Test image modalities RGB
Description

Method:

PoseDETR is an end-to-end, single-stage RGB-only method for direct 6D pose estimation. The approach jointly predicts object instances and their 6D poses. The method does not rely on any default detection or segmentation modules and applies no subsequent iterative pose refinement. A single model per dataset is trained for all objects.

Training Data:

Only provided PBR splits

Used 3D models:

Default object models

Authors:

Temporary Anonymity

Computer specifications GPU: NVIDIA GeForce RTX 4090, CPU: Ryzen 5 3600, Torch-TensorRT (FP16)