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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 3
Unsupervised Semantic Segmentation With 3
评估指标
mIoU
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
mIoU
Paper Title
Repository
TCL
24.0
Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
-
TTD (MaskCLIP)
32.0
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
-
ReCo+
24.2
ReCo: Retrieve and Co-segment for Zero-shot Transfer
-
CLIPpy ViT-B
18.1
Perceptual Grouping in Contrastive Vision-Language Models
-
MaskCLIP
10.0
Extract Free Dense Labels from CLIP
-
Trident
47.6
Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
-
ReCo
19.3
ReCo: Retrieve and Co-segment for Zero-shot Transfer
-
TTD (TCL)
27.0
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
-
COSMOS ViT-B/16
34.7
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
-
ProxyCLIP
42.0
ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
-
TagAlign
27.5
TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
-
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