Comments (1)
Hiii,
We value your feedback.
Since we implement TLC in our SparseGSA, the model runs at various speeds with and without TLC.
While the model will have a faster inference time and similar performance in various benchmark datasets (Set5, Set14, B100), with a decrease in Urban100 and Manga109, without the use of the TLC. On the other side, The TLC enhances the performance in PSNR of some datasets while sacrificing the inference speed.
We will provide a thorough table of quantitative evaluations and the running time of our model with and without TLC in the supplementary. Additionally, we'll standardize our codes as soon as we can and deliver more thorough material (config file and pretrain models of lightweight models).
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Related Issues (19)
- PSNR and SSIM HOT 2
- About model code HOT 2
- Figure 6 from your paper. HOT 2
- Train & Test Configs for Tiny/Small Models HOT 1
- Question about TLC
- which path will the trained model be stored
- SR results
- The arch file
- lightweight pre-trained model
- ModuleNotFoundError: No module named 'basicsr.archs.vgg_arch'
- about code HOT 2
- about arch HOT 8
- code release? HOT 1
- Can you share the pre-trained model? HOT 1
- Problem with Basic_SR_inference_DFDNET and a question about DFDNET HOT 2
- light-version options HOT 1
- where is file for inference with DLGSANet ? HOT 2
- The data for test is missing. HOT 2
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