This is the Linux app named vid2vid whose latest release can be downloaded as vid2vidsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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vid2vid
DESCRIPTION
vid2vid is a deep learning framework for high-resolution video-to-video translation that generates photorealistic videos from structured inputs such as semantic maps, pose sequences, or edge maps. Built on top of image-to-image translation techniques like pix2pixHD, it extends these ideas into the temporal domain by ensuring consistency across video frames. The system can synthesize complex outputs such as realistic talking faces, human motion animations, or dynamic street scenes by learning temporal relationships between frames. It uses generative adversarial networks combined with temporal modeling strategies to maintain coherence and reduce flickering artifacts. The framework is capable of producing high-resolution outputs and is widely used in research related to video synthesis, animation, and simulation. It also supports diverse input modalities, making it flexible for different types of video generation tasks.
Features
- Video-to-video translation from semantic or structured inputs
- Photorealistic high-resolution video synthesis
- Temporal consistency across generated frames
- Support for pose-based and edge-based video generation
- GAN-based architecture for realistic outputs
- Flexible input modalities for diverse applications
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/vid2vid.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
