RefCOCO Segmentation Evaluation:
| Dataset | Split | MLCD-seg-7B | EVF-SAM | GLaMM | VisionLLM v2 | LISA |
|---|---|---|---|---|---|---|
| RefCOCO | val | 83.6 | 82.4 | 79.5 | 79.2 | 74.9 |
| RefCOCO | testA | 85.3 | 84.2 | 83.2 | 82.3 | 79.1 |
| RefCOCO | testB | 81.5 | 80.2 | 76.9 | 77.0 | 72.3 |
| RefCOCO+ | val | 79.4 | 76.5 | 72.6 | 68.9 | 65.1 |
| RefCOCO+ | testA | 82.9 | 80.0 | 78.7 | 75.8 | 70.8 |
| RefCOCO+ | testB | 75.6 | 71.9 | 64.6 | 61.8 | 58.1 |
| RefCOCOg | val | 79.7 | 78.2 | 74.2 | 73.3 | 67.9 |
| RefCOCOg | test | 80.5 | 78.3 | 74.9 | 74.8 | 70.6 |
Evaluation
Install the evaluation tool and execute the evaluation script:
git clone https://github.com/deepglint/unicom/tree/main
cd downstream
bash ./eval/scripts/eval_refcoco.sh
Citations
@misc{mlcdseg_wukun,
author = {Wu, Kun and Xie, Yin and Zhou, Xinyu and An, Xiang, and Deng, Jiankang},
title = {MLCD-seg-7B},
year = {2024},
url = {https://github.com/deepglint/unicom/tree/main/downstream},
}