Flow Guided Transformer

Flow-guided transformers represent a novel approach to generative modeling and other tasks by integrating the power of transformers with information derived from optical flow fields. Current research focuses on improving model architectures, such as incorporating flow information into attention mechanisms to enhance performance in high-resolution image and video synthesis, as well as in tasks like video inpainting and optical flow estimation. This approach shows promise for improving the accuracy and efficiency of various computer vision and generation tasks, leading to more realistic and detailed outputs, and offering enhanced explainability in certain applications like urban flow prediction.