Dataset Card for Latent Diffusion Super Sampling
Image datasets for building image/video upscaling networks.
This repository contains implementation of training and inference code for models trained on the following works:
Part 1: Trained Sub-Pixel Convolutional Network for Upscaling on 5000 individual 720p-4K and 1080p-4K image pairs
References: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network, Shi et al
Shi, W., Caballero, J., Huszár, F., Totz, J., Aitken, A.P., Bishop, R., Rueckert, D. and Wang, Z., 2016.
Results:
720p images tested: 100
Average PSNR: 40.44 dB
1080p images tested: 100
Average PSNR: 43.05 dB
This outperforms the model in the proposed architecture (average is 28.09 dB)
Refer points 5,6,7 in Section "Dataset Description" for further information
Part 2: Trained Convolutional Neural Network Video Frame Interpolation via Spatially-adaptive Separable Convolution for realtime 4K, 1080p and 720p videos
References: Video Frame Interpolation via Adaptive Separable Convolution, Niklaus et al
sniklaus@pdx.edu, mtlong@cs.pdx.edu, fliu@cs.pdx.edu
Results:
720p Model:
•PSNR: 28.35
•SSIM: 0.78
1080p Model:
•PSNR: 29.67
•SSIM: 0.84
4K Model:
•PSNR: 33.74
•SSIM: 0.83
Refer points 8,9,10 in Section "Dataset Description" for further information
Part 3: Latent Diffusion Super Sampling coming soon!!!
Stay tuned>>>>>>>>>>>>>>>
Dataset Details
Consists of 300,000 ground truth 720p and 1080p frames with corresponding 4K output frames
Dataset Sources
YouTube
Uses
Diffusion networks, CNNs, Optical Flow Accelerators, etc.
Dataset Structure
- All images are in .jpg format
- Images are named in the following format: resolution_globalframenumber.jpg
- Resolution refers to either of 3: 720p, 1080p or 4K
- Globalframenumber is the frame number of the image under the respective resolution. eg: 4K_10090.jpg
Curation Rationale
- To build a real-time upscaling network using latent diffusion supersampling.
- Design algorithms for increasing temporal resolution (framerate up-conversion) of videos in real-time.
Dataset Card Authors
Alosh Denny
Dataset Card Contact
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