AI Assisted Motion Animation
FILM or Frame Interpolation for Large Scene Motion is a high-quality frame interpolation neural network powered by Tensorflow 2. It generates frames between two existing images to create an animation seamlessly, without using additional pre-trained networks, like optical flow or depth. FILM is a single-network approach that achieves state-of-the-art results, thanks to its multi-scale feature extractor. The model is trainable from frame triplets alone, using shared convolution weights across the scales. FILM's implementation is available on GitHub and can be used with an API on Replicate Paper, YouTube, and Benchmark Scores. If found useful, the implementation can be cited using appropriate acknowledgment at conferences or publications.
Features:
- High-quality frame interpolation neural network
- Generates frames between two existing images to create a seamless animation
- No need to use additional pre-trained networks, such as optical flow or depth
- Uses a multi-scale feature extractor and shared convolution weights across scales
- Trainable from frame triplets alone
- Available implementation on GitHub
- API integration with Replicate Paper, YouTube, and Benchmark Scores
- Citable implementation at conferences or publications.