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Object Detection On Pku Ddd17 Car

Metrics

mAP50

Results

Performance results of various models on this benchmark

Model Name
mAP50
Paper TitleRepository
ECANet82.2ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
CBAM81.9CBAM: Convolutional Block Attention Module
DCF83.4Calibrated RGB-D Salient Object Detection
CMX80.4CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
EFNet83.0Event-Based Fusion for Motion Deblurring with Cross-modal Attention
SAGate82.0Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
FPN-Fusion81.9Fusing Event-based and RGB camera for Robust Object Detection in Adverse Conditions-
SSD73.1SSD: Single Shot MultiBox Detector
SPNet84.7Specificity-preserving RGB-D Saliency Detection
CAFR86.7Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection
SENet81.6Squeeze-and-Excitation Networks
RENet81.4RGB-Event Fusion for Moving Object Detection in Autonomous Driving
YOLOv481.3YOLOv4: Optimal Speed and Accuracy of Object Detection
RAMNet79.6Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
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Object Detection On Pku Ddd17 Car | SOTA | HyperAI