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Semantic Segmentation On Trans10K

Métriques

GFLOPs

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	GFLOPs	Paper Title	Repository
U-Net	124.55	U-Net: Convolutional Networks for Biomedical Image Segmentation
PSPNet	187.03	Pyramid Scene Parsing Network
ICNet	10.64	ICNet for Real-Time Semantic Segmentation on High-Resolution Images
DeepLabV3+	37.98	Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
OCNet	43.31	OCNet: Object Context Network for Scene Parsing
DANet	198.00	Dual Attention Network for Scene Segmentation
Trans4Trans (M)	34.38	Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World
BiSeNet	19.91	BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
Trans2Lab	61.31	Segmenting Transparent Objects in the Wild
DenseASPP	36.20	DenseASPP for Semantic Segmentation in Street Scenes	-
Trans2Seg	49.03	Segmenting Transparent Object in the Wild with Transformer
FCN	42.23	Fully Convolutional Networks for Semantic Segmentation
RefineNet	44.56	RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Trans4Trans (T)	10.45	Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World
Trans4Trans (S)	19.92	Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World

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