jonnys1226 / ego4d_asl

code for Ego4D Workshop@CVPR 2023 - 1st in MQ & 2nd in NLQ challenge

Hi there 👋

• 🌱 CVer.
• 😄 Multimodal, Video Understanding.

ego4d_asl's Issues

Data/Feature download command

Hi,

Thank you for your contribution. Could you please provide the bash command for downloading data and features for the MQ task? I was planning to use the following:

ego4d --output_directory="ego4d_data" --datasets clips annotations omnivore_video_swinl slowfast8x8_r101_k400 --benchmarks mq --version v2

Best regards,
Arda

When will the NLQ code be released?

Hi, great work, when is the NLQ code scheduled to be released?

Reproducing the MQ results

Hello,

In your paper, you mentioned that your final submission for the MQ Task on eval.ai is produced by ensembling predictions from three models. Could you please provide the config files for these three models? I am also confused about the combination of the features I should use. Is it EgoVLP+InternVideo or EgoVLP+InternVideo+SlowFast+Omnivore?

Edit: When I followed the instructions under "Train on MQ (Train + val)" and "Submission (to Leaderboard test-set server)" in the README file, I got the following scores on eval.ai for the test split:

{"Recall@1x,tIoU=0.5": 43.15983417779825, "average_mAP": 26.092527253173575}

How many V100 GPUs did you use? And how long was the training?

Hello.

Thank you for publishing your project.

As the title says, I would like to know about the number of V100 GPUs and training time.