HyperAI
AccueilActualitésArticles de recherche récentsTutorielsEnsembles de donnéesWikiSOTAModèles LLMClassement GPUÉvénements
Recherche
À propos
HyperAI

Unsupervised Semantic Segmentation With 9

Métriques

mIoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
mIoU
Paper TitleRepository
MaskCLIP16.4Extract Free Dense Labels from CLIP
TCL22.4Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
TTD (MaskCLIP)19.4TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
COSMOS ViT-B/1623.2COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
TagAlign25.3TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
ReCo14.8ReCo: Retrieve and Co-segment for Zero-shot Transfer-
Trident28.6Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
TTD (TCL)23.7TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
ProxyCLIP26.8ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
GroupViT11.1GroupViT: Semantic Segmentation Emerges from Text Supervision
0 of 10 row(s) selected.