Comments (3)
Hi - thank you for your interests. We will be working on D2 + ConvNeXt, and hopefully new results on other datasets too (such as LVIS). While we don't have a concrete timeline, please stay tuned!
from convnext.
Thanks for the quick response. I look forward to the D2 version of results.
from convnext.
Hi - thank you for your interests. We will be working on D2 + ConvNeXt, and hopefully new results on other datasets too (such as LVIS). While we don't have a concrete timeline, please stay tuned!
Have you guys concrete timeline?
from convnext.
Related Issues (20)
- head layer can't be replaced in convnex like other(classifier layer) pytorch model? HOT 1
- Ask for release model on COCO
- Infinite loss value when training under amp HOT 1
- Why LayerNorm before conv in downsampling layers ?
- Error in Convnext training with Swin transformer framework - The testing results of the whole dataset is empty.
- Hyperparameter setting for training from scratch on CIFAR-10 HOT 9
- can convNext add deformable conv in the block
- LayerNorm, what is going on? HOT 1
- load pretrained model, there are errors. RuntimeError: Error(s) in loading state_dict for ConvNeXt: Missing key(s) in state_dict HOT 1
- Tensorrt Model?
- input dimensions
- Welcome update to OpenMMLab 2.0
- A warning appears in DDP using ConvNeXt HOT 1
- Missing code or wrong reference HOT 2
- Finetuning on Imagenet100 using ConvNeXt-T for ImageNet1k
- I can not use 'timm.create_model' to create my convnext HOT 1
- convnext_tiny Loss not change HOT 1
- Error:0.3.2timm.create_model did not have layer_scale_init_value
- How can I make predictions on my testing dataset for using command line?
- Resize Test Images for size less than 32
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from convnext.