maudzung/TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch

The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project could be found here (from the authors) Training much faster, achieve 120 FPS in the inference phase on a single GPU (GTX1080Ti). The implementation could achieve comparative results with the reported results in the TTNet paper. There are several limitations of the TTNet Paper (hints: Loss function, input size, and 2 more). I have implemented the task with a new approach and a new model. By default (as the above command), there are 4 modules in the TTNet model: global stage, local stage, event spotting, segmentation.