MCG-NJU / VideoMAE

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
https://arxiv.org/abs/2203.12602
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MoCoV3 Training Configuration #87

Open fmthoker opened 1 year ago

fmthoker commented 1 year ago

Hi, Thanks for releasing the code and this amazing work. I am using the MAE and MoCo-V3 baseline in my current work however I can't reproduce your results in Table 2 with Moco-V3 pre-train on UCF --> Finetune-UCF( 81.7 %). There are no implementations/configuration details about this setting in your paper, would it be possible to share how you pre-train MoCo-V3? I am also strictly following image-based MoCo-V3. Details like batch size, learning rates, learning scheduling and number of GPUS would be helpful. Thanks and looking forward to your reply.