We introduce a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance.
Ranked #1 on Video Matting on VideoMatte240K
We introduce Merlion, an open-source machine learning library for time series.
Generative Adversarial Networks (GANs) can generate near photo realistic images in narrow domains such as human faces.
Ranked #1 on Unconditional Image Generation on ImageNet 128x128
It is the result from the merger of the two most popular packages for stream learning in Python: Creme and scikit-multiflow.
Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general real-world degraded images.
Furthermore, based on LibFewShot, we provide comprehensive evaluations on multiple benchmark datasets with multiple backbone architectures to evaluate common pitfalls and effects of different training tricks.
Our framework, dubbed StyleCariGAN, automatically creates a realistic and detailed caricature from an input photo with optional controls on shape exaggeration degree and color stylization type.