Comments (2)
huang-ziyuan
commented on May 28, 2024
Thanks for the attention. I am not sure which model are you referring to, but you can simply half the batch size when using 32 frames instead of 16 frames as the input.
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PeiqinZhuang
commented on May 28, 2024
Thank you for your answer. I will try to half the batch size.
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Related Issues (20)
- Issue on running on sthv2 HOT 2
- Problems on loading imagenet weight HOT 1
- features HOT 2
- Use TAdaConv in Video Object Detection? HOT 1
- How to use R(2+1)D with TAda? HOT 1
- some questions about flops and inference time HOT 1
- TAdaConvNeXt-T HOT 3
- Frame description and temporal modeling HOT 1
- Applying TadaConv HOT 1
- Batch-wise and Temporal-wise modeling HOT 1
- I am curious about why the flops and parms of TAdaConvNeXt-T is one half of the ResNet50's, to my knowledge they should be similar. HOT 2
- apply AdaConv to P3D or SlowFast HOT 1
- Applying TAdaConv3d to Timesformer HOT 2
- top1-5 accuracy did not achieve the expected effect（Mosi/Finetuned on UCF101/HMDB51 dataset） HOT 12
- TAdaConv2d needs in_channels to equal out_channels HOT 1
- In Mosi, training on hmdb51 based on the pre trained checkpoint you provided cannot reproduce the results HOT 1
- Feedback on the issue of ema coefficient. HOT 5
- Question on reproducing the results on sthv2
- RuntimeError: Error(s) in loading state_dict for BaseVideoModel: size mismatch for head.out.weight: copying a param with shape torch.Size([400, 768]) from checkpoint, the shape in current model is torch.Size([5, 768]). size mismatch for head.out.bias: copying a param with shape torch.Size([400]) from checkpoint, the shape in current model is torch.Size([5]). HOT 1
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