Table for cross-model transferability among commonly used detection models (in mAP) of various-sized YOLO's, Faster R-CNN, RetinaNet, and Swin Transformer, at confidence thresholds of 0.50, validating ...

12/29/2022 Nvidia 's FasterTransformer now supports Swin Transformer V2 inference, which have significant speed improvements on T4 and A100 GPUs. 11/30/2022 Models and codes of Feature Distillation ...

Despite the many advantages of Convolutional Neural Networks (CNN), their perceptual fields are usually small and not conducive to capturing global features. In contrast, Transformer is able to ...

With the rapid development of society, crowded scenes can be seen almost everywhere. Therefore, it is important to accurately predict the number and density distribution of people in those crowded ...

The prediction of the projected density of states (PDOS) in materials has traditionally relied on deep learning models based on graph convolutional networks (GCN) and Graph Attention Networks (GAT).