Recently, Graph Convolution Network (GCN) and Temporal Convolution Network (TCN) are introduced into traffic prediction and achieve state-of-the-art performance due to their good ability for modeling ...

Abstract: Diabetic retinopathy (DR) grading is complex because it requires recognizing intra and interclass variations, handling skewed data distributions, and identifying microaneurysms. Accurate DR ...

Visual multi-vessel tracking is critical for intelligent maritime surveillance yet challenging due to the complexity of efficiently modeling rigid vessel structures across diverse scales and ...

Deconvolution as a research area focuses on developing and analyzing mathematical and computational methods to invert convolution operations, typically to recover latent signals, images, or ...

This repository contains official implementation of Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes in CVPR 2020, by Huanjing Yue, Cong Cao, Lei Liao, Ronghe Chu, and Jingyu ...