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SOTA
Fussgängererkennung
Pedestrian Detection On Llvip
Pedestrian Detection On Llvip
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AP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
AP
Paper Title
MMPedestron
0.726
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset
MiPa
0.665
MiPa: Mixed Patch Infrared-Visible Modality Agnostic Object Detection
CFT
0.636
Cross-Modality Fusion Transformer for Multispectral Object Detection
UniRGB-IR
0.632
UniRGB-IR: A Unified Framework for Visible-Infrared Semantic Tasks via Adapter Tuning
RSDet
0.613
Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection
CMX
0.596
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
CSSA
0.592
Multimodal Object Detection by Channel Switching and Spatial Attention
GAFF
0.558
Multimodal Object Detection by Channel Switching and Spatial Attention
Halfway Fusion
0.551
Multimodal Object Detection by Channel Switching and Spatial Attention
YoloV5-RGB
0.527
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
ProbEn
0.515
Multimodal Object Detection via Probabilistic Ensembling
ProbEn
0.515
Multimodal Object Detection by Channel Switching and Spatial Attention
YoloV3-RGB
0.466
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
INSANet
-
INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection
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Pedestrian Detection On Llvip | SOTA | HyperAI