WebJan 16, 2024 · A decoupled head with three branches for flame objects is introduced. In addition to the classification and regression branches, an object score branch is added to predict the likelihood of an object being a flame or other objects. Based on dynamic attention and decoupled head, the DANet for flame detection is proposed. WebUnifying Short and Long-Term Tracking with Graph Hierarchies ... Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution Jiahao Chen · Bing …
lif314/NeRFs-CVPR2024 - Github
WebDynamic Head: Unifying Object Detection Heads with Attentions Xiyang Dai, Yinpeng Chen, Bin (Leo) Hsiao, Dongdong Chen, Mengchen Liu, Lu Yuan, Lei Zhang . CVPR 2024 June 2024 . View Publication. Unsupervised Pre-training for Person Re-identification WebAug 26, 2024 · Moreover, high-speed and low-altitude flight bring in the motion blur on the densely packed objects, which leads to great challenge of object distinction. To solve the two issues mentioned above, we propose TPH-YOLOv5. Based on YOLOv5, we add one more prediction head to detect different-scale objects. highlighting system for notes
DynamicDet: A Unified Dynamic Architecture for Object Detection
WebAn object detection benchmark was established using the HIOD dataset and eight state-of-the-art object detectors. The benchmark provides a comprehensive evaluation of the performance of the selected object detectors on a large and diverse set of images of objects commonly seen in hospital environments. ... Dynamic head: Unifying object ... WebJun 7, 2024 · The complex nature of combining localization and classification in object detection has resulted in the flourished development of methods. Previous works tried to … Web5. Dynamic Head: Unifying Object Detection Heads with Attentions. 6. Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection. 7. UP-DETR: Unsupervised Pre-training for Object Detection with Transformers. 8. MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. 9. highlighting thin fine hair