amanchadha / iSeeBetter

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
https://arxiv.org/abs/2006.11161
MIT License
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Results on Vid4 #5

Closed yuangan closed 4 years ago

yuangan commented 4 years ago

Hi, I've tested your model weights/netG_epoch_4_1.pth, and I can't get the result of 26.57/0.773 on Foliage datasets. I just got Avg PSNR Predicted = 25.728. Could you tell me how to get it? Besides, the result of City is also under 26. These are my arguments: Namespace(chop_forward=False, data_dir='./Vid4', debug=False, file_list='city_test.txt', future_frame=True, gpu_mode=False, gpus=1, model='weights/netG_epoch_4_1.pth', model_type='RBPN', nFrames=7, other_dataset=True, output='Results/', residual=False, seed=123, testBatchSize=1, threads=1, upscale_factor=4)

PS: Could you offer the augmented dataset? Thanks very much!

amanchadha commented 4 years ago

Hey!

Sorry for the delayed response. From your parameters, it looks like a couple of things are off:

Hope this helps!