SYLan2019

DSTAGNN. DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting, which is accepted at ICML2022.

Transformer-Gan-Anomaly-Detection. A Transformer-based GAN for Anomaly Detection, International Conference on Artificial Neural Networks, (ICANN2022).

MH-ASTIGCN. MULTI HEAD SELF-ATTENTION BASED SPATIAL-TEMPORAL INFORMATION GRAPH CONVOLUTIONAL NETWORKS FOR TRAFFIC FLOW FORECASTING

Skip-Attention-GAN. This repository contains PyTorch implementation of the following paper: SAGAN: SKIP-ATTENTION GAN FOR ANOMALY DETECTION.

STDOD. A visual object tracking method where we take into account the difference between occlusion and self-deformation in a spatial-temporal regularised DCF filter. Robust Visual Object Tracking with Spatiotemporal Regularisation and Discriminative Occlusion Deformation, International Conference on Image Processing (ICIP). IEEE, 2021, pp. 1879-1883.

DLAHSD. DLAHSD: Dynamic label adopted in auxiliary head for SAR detection. An efficient SAR-ship detector based on center point.

STGFMamba. STGFMamba: Spatio-Temporal Graph Fourier-Enhanced Mamba for Traffic Flow Prediction

DSTFGCN. DSTFGCN: A Dynamic Spatial-temporal Fusion Graph Convolution Network for Traffic Flow Forecasting

MRRNet. This repository contains PyTorch implementation of the following paper: Face Super-Resolution with Spatial Attention Guided by Multiscale Receptive-Field Features.

SANF-AD. A SEMANTICS-AWARE NORMALIZING FLOW MODEL FOR ANOMALY DETECTION

VHKOR. Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer

DBGNN. A dual branch graph neural network for spatial interpolation in traffic scene

GanNeXt. GanNeXt: A New Convolutional GAN for Anomaly Detection

MLP-MHCA. This is a visual object tracker which is a modified version of the python framework TransT based on Pytorch, also borrowing from PySOT. We would like to thank their authors for providing great frameworks and toolkits.

TDVGCN. Two-stage Dual-View Graph Convolution Network for Spatial Interpolation in Traffic Scene

MADFlow. MADFlow: Multimodal Difference Compensation Flow for Multimodal Anomaly Detection

SOD-DEDDH. Small Object Detection Using Detail Enhancement and Decoupled Detection Head

FOAD-MFFF. Flow-based one-class anomaly detection with Multi-frequency Feature fusion. (ICIP 2023)

STDMSI. STDMSI: Dual-Stage Spatio-Temporal Dependency Modeling for Spatial Interpolation in Traffic Scene

DNFAD. Dual-branch Normalizing Flow for Anomaly Detection and Localization from Images