Flowframes

Flowframes is an application that uses artificial intelligence to interpolate video frames, producing smoother motion by generating additional images between existing ones. It is designed for users who need higher frame rates or slow-motion results without re-recording or re-rendering footage. The software analyzes motion and visual changes across frames, predicting how objects move to create missing frames. It supports multiple AI-based interpolation models and can be used for films, gameplay footage, or animation projects.

Core Functions and Workflow

Flowframes works as a local processing tool where users select input videos, choose an interpolation method, and export the processed result. It supports different AI models such as RIFE, DAIN, and FLAVR, each optimized for particular content types and hardware. The software runs on a range of GPUs and uses either CUDA or Vulkan depending on system setup. Its workflow is simple but adaptable, allowing both newcomers and experienced users to adjust performance and quality balance according to system capabilities.

Main Features and User Options

When working with Flowframes, the typical process involves:

•         Loading a video file or image sequence into the application.
•         Selecting the preferred AI model based on speed or accuracy needs.
•         Adjusting output frame rate and resolution settings.
•         Enabling duplicate-frame removal or scene-change detection if necessary.
•         Exporting the final video in a supported format such as MP4 or WEBM.

This structure lets users optimize processing speed while preserving visual stability, giving flexibility for different video sources and goals.

Performance and Use Cases

The efficiency of Flowframes depends on system resources and content complexity. High-motion scenes, camera pans, or detailed animations may require more processing time and careful model selection. Users apply the software in several contexts: improving gameplay recordings, converting 30 FPS footage to 60 FPS, or restoring low-frame-rate videos to achieve smoother playback. Animators use it to generate intermediate frames, while editors apply it for motion consistency in slow-motion segments. The output quality varies with model type and GPU performance, but predictable results can be achieved through testing and adjustment.