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홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

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Object Detection On Pku Ddd17 Car

평가 지표

mAP50

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	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	-
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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Object Detection On Pku Ddd17 Car | SOTA | HyperAI초신경