HyperAI
HyperAI
الرئيسية
المنصة
الوثائق
الأخبار
الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
شروط الخدمة
سياسة الخصوصية
العربية
HyperAI
HyperAI
Toggle Sidebar
البحث في الموقع...
⌘
K
Command Palette
Search for a command to run...
المنصة
الرئيسية
SOTA
التمييز الدلالي
Semantic Segmentation On Pascal Context
Semantic Segmentation On Pascal Context
المقاييس
mIoU
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
mIoU
Paper Title
VPNeXt
71.1
VPNeXt -- Rethinking Dense Decoding for Plain Vision Transformer
PlainSeg (EVA-02-L)
71.0
Minimalist and High-Performance Semantic Segmentation with Plain Vision Transformers
InternImage-H
70.3
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
RSSeg-ViT-L (BEiT pretrain)
68.9
Representation Separation for Semantic Segmentation with Vision Transformers
ViT-Adapter-L (Mask2Former, BEiT pretrain)
68.2
Vision Transformer Adapter for Dense Predictions
ViT-Adapter-L (UperNet, BEiT pretrain)
67.5
Vision Transformer Adapter for Dense Predictions
RSSeg-ViT-L
67.5
Representation Separation for Semantic Segmentation with Vision Transformers
SegViT (ours)
65.3
SegViT: Semantic Segmentation with Plain Vision Transformers
CAA + CAR (ConvNeXt-Large + JPU)
64.1
CAR: Class-aware Regularizations for Semantic Segmentation
SenFormer (Swin-L)
64.0
Efficient Self-Ensemble for Semantic Segmentation
Sequential Ensemble (Segformer + HRNet)
62.1
Sequential Ensembling for Semantic Segmentation
CAA + Simple decoder (Efficientnet-B7)
60.5
Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation
DPT-Hybrid
60.46
Vision Transformers for Dense Prediction
CAA (Efficientnet-B7)
60.1
Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation
HRNetV2 + OCR + RMI (PaddleClas pretrained)
59.6
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
Seg-L-Mask/16
59.0
Segmenter: Transformer for Semantic Segmentation
ResNeSt-269
58.9
ResNeSt: Split-Attention Networks
DEPICT-SA (ViT-L multi-scale)
58.6
Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective
ResNeSt-200
58.4
ResNeSt: Split-Attention Networks
DEPICT-SA (ViT-L single-scale)
57.9
Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective
0 of 66 row(s) selected.
Previous
Next
Semantic Segmentation On Pascal Context | SOTA | HyperAI