PointFusion在检测之前先融合全局图像和点云特征,MSMDFusion在多个尺度上融合激光雷达和RGB特征。[35]提出了一种多任务网络,同时考虑2D和3D目标检测、地面估计和深度补全。TransFusion和BEVFusion在BEV空间使用多头自注意力融合特征。尽管 Transformer 在检测常见物体方面取得了成功,[42]发现TransFusion在检测罕见类别时表现不...
In YOLOv7, the feature pyramid network (FPN) of the neck stage is constructed through continuous upsampling and skip connections for feature fusion, after continuous downsampling of the backbone. However, this process can result in the loss of precise shallow position information. To tackle this ...
其中Precision 表示为"P",Recall 表示为"R",YOLOv7+BRA比YOLOv7系列模型具有更高的 Precision结果。从mAP@̃0.5结果来看,YOLOv7+BRA模型优于 YOLOv7系列模型和YOLOv5m模型,与第二名模型相差2.2%。在 mAP@0.9方面,YOLOv7+BRA模型优于所有其他YOLO系列模型,除了YOLOv7-E6具有更复杂的网络结构并且需要更多的...
YOLOv7-based insulator defect detection with progressive feature fusion and DFC attention 来自 IOP 喜欢 0 阅读量: 8 作者:X You,J Ma 摘要: With the development of smart grids, drones have been widely used for inspecting power transmission lines, generating a large amount of insulator image ...
简介:YOLO还真行 | 2D检测教3D检测做事情,YOLOv7让BEVFusion无痛涨6个点,长尾也解决了 自动驾驶车辆(AVs)必须准确检测来自常见和罕见类别的物体,以确保安全导航,这催生了长尾3D目标检测(LT3D)的问题。当代基于激光雷达(LiDAR)的3D检测器在罕见类别上的表现不佳(例如,CenterPoint仅在_stromler_上达到5.1 AP),...
YOLOv7sub-pixel convolutionfeature fusionIn recent years, significant progress has been witnessed in the field of deep learning-based object detection. As a subtask in the field of object detection, traffic sign detection has great potential for development. However, the existing object detection ...
In this paper, we propose MFPIDet, a novel prohibited item detection neural network architecture based on improved YOLOV7 to achieve reliable prohibited item detection in complex environments. Specifically, a multi-scale attention module (MAM) backbone is proposed to filter the redundant information...
Finally, we fused the results from YOLOv7 CrowdHuman, SlowFast, and DeepSort models to obtain student classroom behavior data. We conducted experiments on the SCB-Dataset, and YOLOv7+BRA achieved an mAP@0.5 of 87.1%, resulting in a 2.2% improvement over previous results. Our SCB-dataset ...
Thus, in this study, we proposed a water surface dynamic multi-target tracking algorithm based on the fusion of YOLOv7 and DeepSORT. The algorithm first introduces the super-resolution reconstruction network. The network can eliminate the interference of clouds and waves in images to improve the...
Additionally, marine target detection is challenging due to multi-scale problems from varying target-to-device distances, complex target clustering, and noise from waterborne particulates.To address these issues, we propose MTD-YOLOv5.Initially, we enhance image contrast with grayscale equalization and ...