Search Results for "network"

Shotcut is a free, open source, cross-platform video editor for Windows, Mac and Linux. Major features include support for a wide range of formats; no import required meaning native timeline editing; Blackmagic Design support for input and preview monitoring; and resolution support to 4k. Copyright © 2011-2023 by Meltytech, LLC Shotcut is a trademark of Meltytech, LLC.

Sharpen your low-resolution pictures with the power of AI upscaling. SuperImage is a neural network-based image upscaling build with the MNN deep learning framework and the Real-ESRGAN algorithm. By leveraging the power of your device's GPU, SuperImage is able to upscale and restore the details of your images without uploading them to the internet, keeping your data secure. SuperImage is a neural network-based image upscaling application for Android built with the MNN deep learning framework and Real-ESRGAN. ...

...To improve the quality of the texture, it is first Upscaled using RealESRGAN. The user can select scaling factor: x2, x4 or x8. After the Upscaling procedure, the texture is deblured using the Scale-recurrent Network for Deep Image Deblurring. An example of a processed texture is shown in the following image (parameters used: scaling-factor = 4 and deblur iterations = 4) besides upscaling and debluring the utility also generates normal maps for each texture. This is implemented using the DeepBump by HugoTiny model. Examples of normal maps are shown in the following images.

Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage.

...Unlike most existing methods that perform video matting frame-by-frame as independent images, our method uses a recurrent architecture to exploit temporal information in videos and achieves significant improvements in temporal coherence and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. Our method does not require any auxiliary inputs such as a trimap or a pre-captured background image, so it can be widely applied to existing human matting applications. RVM is specifically designed for robust human video matting.

...While debugged, a few lingering issues may remain, if you encounter any please submit them and they will be resolved. The sources and features of the project can be found in the wiki. Before use, one should verify that the network architecture is as-desired. This may be done with the GUI to the right of the number display. The "Default" button resets the network to hard-coded values which I have verified function. The "Reset" button sets the ACTIVE network to whatever architecture is displayed. In order to change which network is displayed, use the "Critic [1] or Generator [0]" checkbox. ...