Search Results for author:
Found 2 papers, 1 papers with code
Enhancing Traffic Scene Predictions with Generative Adversarial Networks
This ensures the quality of the predicted frames to be sufficient to enable accurate detection of objects, which is especially important for autonomously driving cars.
FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing GANs
The main advantage of the FutureGAN framework is that it is applicable to various different datasets without additional changes, whilst achieving stable results that are competitive to the state-of-the-art in video prediction.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
