Unsupervised Video Interpolation Using Cycle Consistency
Explore advanced techniques in unsupervised video interpolation using cycle consistency in this 30-minute lecture from the University of Central Florida. Delve into frame interpolation methods, including sparse optical flow and bi-directional flow-guided interpolation. Examine the limitations of supervised architectures like Super SloMo and discover how unsupervised approaches overcome these challenges. Learn about cycle consistency GANs, time domain consistency constraints, and pseudo-supervised loss functions. Analyze experimental setups, datasets, and evaluation methods used to test low-resolution training, domain gap testing, and fine-tuning for domain transfer. Gain insights from qualitative results and ablation studies on optimal weights, enhancing your understanding of cutting-edge video interpolation techniques.