We provide the scripts as well as the trained models on the downstream tasks as follows. Note that before you run the finetuning scripts, you need to download the corresponding pretrained ROSITA model here.
The following script run the finetuning on the train+trainval
split of VQAv2.
$ bash scripts/train-vqa-vqav2.sh
As the training stage complete, you may run the following script to run evaluation on the test
split and generate a result.json
file under the output folder. This file can be submitted to the online server to obtain the performance.
$ bash scripts/test-vqa-vqav2.sh
We also provide the checkpoint model to reproduce the following results on test-dev
and test-std
split using the testing script above.
Name | Test-dev | Test-std | Downloads | ||||||
---|---|---|---|---|---|---|---|---|---|
All | Y/N | Num | Other | All | Y/N | Num | Other | ||
ROSITA-base | 73.91 | 89.91 | 56.07 | 64.29 | 73.97 | 89.76 | 55.81 | 64.39 | model |
The following script run the finetuning on the train
split of RefCOCO.
$ bash scripts/train-rec-refcoco.sh
As the training stage complete, you may run the following script to run evaluation on the val/testA/testB
split of RefCOCO.
bash scripts/test-rec-refcoco.sh
We also provide the checkpoint model to reproduce the following results on val
and testA/B
split using the testing script above.
Name | RefCOCO | Downloads | ||
---|---|---|---|---|
val | testA | testB | ||
ROSITA-base | 84.79 | 87.99 | 78.28 | model |
The following script run the finetuning on the train
split of RefCOCO+.
bash scripts/train-rec-refcoco+.sh
As the training stage complete, you may run the following script to run evaluation on the val/testA/testB
split of RefCOCO+.
bash scripts/test-rec-refcoco+.sh
We also provide the checkpoint model to reproduce the following results on val
and testA/B
split using the testing script above.
Name | RefCOCO+ | Downloads | ||
---|---|---|---|---|
val | testA | testB | ||
ROSITA-base | 76.06 | 82.01 | 67.40 | model |
The following script run the finetuning on the train
split of RefCOCOg.
bash scripts/train-rec-refcocog.sh
As the training stage complete, you may run the following script to run evaluation on the val/test
split of RefCOCOg.
bash scripts/test-rec-refcocog.sh
We also provide the checkpoint model to reproduce the following results on val
and testA/B
split using the testing script above.
Name | RefCOCOg | Downloads | |
---|---|---|---|
val | test | ||
ROSITA-base | 78.23 | 78.25 | model |
The following script run the finetuning on the train
split of ITR-COCO.
bash scripts/train-itr-coco.sh
As the training stage complete, you may run the following script to run evaluation on the testall
split of ITR-COCO.
bash scripts/test-itr-coco.sh
We also provide the checkpoint model to reproduce the following results on testall
split using the testing script above.
Name | IR-COCO | TR-COCO | Downloads | ||||
---|---|---|---|---|---|---|---|
R@1 | R@5 | R@10 | R@1 | R@5 | R@10 | ||
ROSITA-base | 54.40 | 80.92 | 88.60 | 71.26 | 91.62 | 95.58 | model |
The following script run the finetuning on the train
split of ITR-Flickr.
bash scripts/train-itr-flickr.sh
As the training stage complete, you may run the following script to run evaluation on the test
split of ITR-Flickr.
bash scripts/test-itr-flickr.sh
We also provide the checkpoint model to reproduce the following results on test
split using the testing script above.
Name | IR-Flickr | TR-Flickr | Downloads | ||||
---|---|---|---|---|---|---|---|
R@1 | R@5 | R@10 | R@1 | R@5 | R@10 | ||
ROSITA-base | 74.08 | 92.44 | 96.08 | 88.90 | 98.10 | 99.30 | model |