Comments (3)
Sorry that I did not have enough time to extract the detection features with IN22K pre-trained models. I'd like to retrain the PDVC model if you could provide your extracted video features of ActivityNet Captions :)
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Sorry that I did not have enough time to extract the detection features with IN22K pre-trained models. I'd like to retrain the PDVC model if you could provide your extracted video features of ActivityNet Captions :)
Thank you for your reply. I just randomly used a few videos to see the performance of the model, so I don't have video features. Because the model does not contain many categories (for example, the animal category only contains dogs and horses), the process of object detection may be problematic when there are categories in the video that are not in ActivityNet. But I noticed that the model works really well if ActivityNet's categories (eg dog and horse) are present in the video. To be honest, pre-training on ImageNet-22k is a very time-consuming process. But your model is really awesome. Thank you very much for your work. Finally, if you have time someday, you can do ImageNet-22k pre-training, which I believe will work better for the model.
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Agree! Thanks for your insightful comments, and I will consider it as future work.
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Related Issues (20)
- 关于实验结果 HOT 5
- Some questions regarding the dataset HOT 2
- Running PDVC on Your Own Videos
- 关于 MultiScaleDeformableAttention 的问题 HOT 1
- A question about demo video HOT 2
- Ablation study of auxiliary losses? HOT 1
- Does the code support multi-gpu training? HOT 1
- 用自己训练的C3D模型进行测试,错误
- Issue on inference HOT 1
- 为什么测试集的loss几乎不变?
- the video is shown with a white screen.
- How do I train my own data set?
- google drive 无法访问内容 HOT 2
- About two stage
- Running PDVC on Your Own Videos predict json file HOT 2
- How to use 2 GPUs? HOT 2
- How to extract C3D features? HOT 2
- test_and_visualize.sh HOT 1
- Inference on caption activitynet test dataset
- 未能复现readme中的实验结果
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