Hello
How are you?
Thanks for contributing this project.
I have a question.
Does this project support class-incremental training for saving training time without catastrophic forgetting?
Let's suppose I've trained a model on the dataset with K classes for 7 days.
If a new class is added into this dataset, should we train a model with the expanded dataset (K+1 classes) from begin?
If so, it is so expensive, especially in case of object detection in retail store.
That's because a new class of good is added frequently in retail store.
Can we train a new model in short time with the original weight on the expanded dataset?
I think that this is a very important function.
I send some recommended papers for this project.
https://arxiv.org/pdf/1708.06977.pdfhttps://arxiv.org/pdf/2003.04668.pdfhttps://arxiv.org/pdf/2003.06957.pdfhttps://arxiv.org/pdf/2003.07304.pdf
Please let me know if you have a willing to implement this.
Thanks
We don't support these works in detection area now.
And I suggest you to modify our code directly, and I believe it is not difficult to implement these works.
Hello How are you? Thanks for contributing this project. I have a question. Does this project support class-incremental training for saving training time without catastrophic forgetting? Let's suppose I've trained a model on the dataset with K classes for 7 days. If a new class is added into this dataset, should we train a model with the expanded dataset (K+1 classes) from begin? If so, it is so expensive, especially in case of object detection in retail store. That's because a new class of good is added frequently in retail store. Can we train a new model in short time with the original weight on the expanded dataset? I think that this is a very important function. I send some recommended papers for this project. https://arxiv.org/pdf/1708.06977.pdf https://arxiv.org/pdf/2003.04668.pdf https://arxiv.org/pdf/2003.06957.pdf https://arxiv.org/pdf/2003.07304.pdf Please let me know if you have a willing to implement this. Thanks