Denis Shiryaev upscaled 60 fps 4k version of 1896 movie "Arrival of a Train at La Ciotat" with several neural networks
https://www.youtube.com/watch?v=3RYNThid23g
https://www.reddit.com/r/videos/comments/eyoxfb/oc_i_have_made_60_fps_4k_version_of_1896_movie/
Upscaled and resounded version of a classic B&W movie: Arrival of a Train at La Ciotat, The Lumière Brothers, 1896
Source used to upscale: https://youtu.be/MT-70ni4Ddo
Algorithms that were used:
››› To upscale to 4k – Gigapixel AI – Topaz Labs https://topazlabs.com/gigapixel-ai/
››› To add FPS – Dain, https://sites.google.com/view/wenbobao/dain
This is the interesting Bit:
Depth-Aware Video Frame Interpolation
Wenbo Bao*, Wei-Sheng Lai#, Chao Ma*, Xiaoyun Zhang*, Zhiyong Gao*, Ming-Hsuan Yang#&
*Shanghai Jiao Tong University, #University of California, Merced, &Google
Abstract
Video frame interpolation aims to synthesize non-existent frames in-between the original frames. While significant advances have been made from the deep convolutional neural networks, the quality of interpolation is often reduced due to large object motion or occlusion. In this work, we propose to explicitly detect the occlusion by exploring the depth cue in frame interpolation. Specifically, we develop a depth-aware flow projection layer to synthesize intermediate flows that preferably sample closer objects than farther ones. In addition, we learn hierarchical features as the contextual information. The proposed model then warps the input frames, depth maps, and contextual features based on the optical flow and local interpolation kernels for synthesizing the output frame. Our model is compact, efficient, and fully differentiable to optimize all the components. We conduct extensive experiments to analyze the effect of the depth-aware flow projection layer and hierarchical contextual features. Quantitative and qualitative results demonstrate that the proposed model performs favorably against state-of-the-art frame interpolation methods on a wide variety of datasets.
Update: Colorized by DeOldify Neural Network version of this video: https://youtu.be/EqbOhqXHL7E
This is an upscaled version of the gorgeous video by Bard Canning of curiosity descent uploaded on Sep 13, 2012,
source: https://youtu.be/Esj5juUzhpU
The video was upscaled with Gigapixel AI software to 4K, frame by frame, 60 FPS was achieved with After Effect frame blending. I made this video for fun, to spread the love of space traveling. Here is my telegram channel: http://t.me/denissexy Here is comparison: https://gfycat.com/diligentgianteaste... Here is a tutorial how to upscale things in Russian language: https://vc.ru/76580 x
