Pedestrian Detection On Llvip

Results

Performance results of various models on this benchmark

		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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