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SOTA
基于语言图像预训练的无监督语义分割
Unsupervised Semantic Segmentation With 4
Unsupervised Semantic Segmentation With 4
评估指标
Mean IoU (val)
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Mean IoU (val)
Paper Title
Repository
COSMOS ViT-B/16
17.7
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
-
TagAlign
17.3
TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
-
TTD (TCL)
17.0
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
-
GroupViT (RedCaps)
9.2
GroupViT: Semantic Segmentation Emerges from Text Supervision
-
ReCo
11.2
ReCo: Retrieve and Co-segment for Zero-shot Transfer
-
Trident
26.7
Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
-
ProxyCLIP
24.2
ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
-
TCL
17.1
Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
-
TTD (MaskCLIP)
12.7
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
-
MaskCLIP
9.8
Extract Free Dense Labels from CLIP
-
CLIPpy ViT-B
13.5
Perceptual Grouping in Contrastive Vision-Language Models
-
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