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View Code? Open in Web Editor NEWOfficial pytorch implementation of paper "RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution"
Official pytorch implementation of paper "RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution"
Hello, I trying to evaluate pre-trained models. But I can't find network configurations for RSTT-M and RSTT-L checkpoints. Can you provide it?
Hello,I am very interested in your work. I want to use this model to train my own dataset,is this possible?
Hi!
In your paper, on Nvidia Quadro RTX 6000, real-time video SR is realized, how much memory does the inference process take?
And, is it possible to realize real-time video SR using RSTT on nvidia v100 card?
Hello! Thank you for releasing the code of your amazing work!
I want to implement some experiments based on your pre-trained weight, but I think that we are not able to resume training from the released checkpoints without its corresponding ".state" file.
Could you please also release the .state files?
Thank you very much!
Hello,Is the extra frame from the decoder just get the average of the adjacent features from the encoder?
if i % 2 == 0:
y[:, i, :, :, :] = x[:, i//2]
else:
y[:, i, :, :, :] = (x[:, i//2] + x[:, i//2 + 1]) / 2
Hi, came across your work by chance. Has this CVPR article been published yet?
I trained my own dataset, but the effect of interpolation is not good. If I do not want to interpolation frames, that is, input_ frame=4,output_ frame=4, how should I modify it?
can i modify the output_frame in the weight of completed training?
Congratulations! very excellent work! But I have a small wonder.
I am a beginner in DL. This question may be stupid.
Shouldn't you call torch.cuda.synchronous() before start?
like this:
you may refer to this tarun005/FLAVR#14
In FLAVR, whether use torch.cuda.synchronous() leads to a significant difference in inference time.
their origin paper(before use this function):
and their current paper(after use this function):
Could you please report your comparison?
Looking forward to your reply. Thank you a lot!
Hello,
MSU Graphics & Media Lab Video Group has recently launched two new Super-Resolution Benchmarks.
If you are interested in participating, you can add your algorithm following the submission steps:
We would be grateful for your feedback on our work!
how can someone test a video on these pre-trained models?
If I change the number of input_nums, from input_frames=4 to input_frames=12, and cancel Interpolation ,will it affect the model results?
In addition, if it is feasible to convert to TensorRT?
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