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SOTA
Object Detection
Object Detection On Pku Ddd17 Car
Object Detection On Pku Ddd17 Car
Métriques
mAP50
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
mAP50
Paper Title
Repository
ECANet
82.2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
CBAM
81.9
CBAM: Convolutional Block Attention Module
DCF
83.4
Calibrated RGB-D Salient Object Detection
CMX
80.4
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
EFNet
83.0
Event-Based Fusion for Motion Deblurring with Cross-modal Attention
SAGate
82.0
Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
FPN-Fusion
81.9
Fusing Event-based and RGB camera for Robust Object Detection in Adverse Conditions
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SSD
73.1
SSD: Single Shot MultiBox Detector
SPNet
84.7
Specificity-preserving RGB-D Saliency Detection
CAFR
86.7
Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection
SENet
81.6
Squeeze-and-Excitation Networks
RENet
81.4
RGB-Event Fusion for Moving Object Detection in Autonomous Driving
YOLOv4
81.3
YOLOv4: Optimal Speed and Accuracy of Object Detection
RAMNet
79.6
Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
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