HyperAI초신경
홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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HyperAI초신경

Unsupervised Semantic Segmentation With 3

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mIoU

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
mIoU
Paper TitleRepository
TCL24.0Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
TTD (MaskCLIP)32.0TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
ReCo+24.2ReCo: Retrieve and Co-segment for Zero-shot Transfer-
CLIPpy ViT-B18.1Perceptual Grouping in Contrastive Vision-Language Models
MaskCLIP10.0Extract Free Dense Labels from CLIP
Trident47.6Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
ReCo19.3ReCo: Retrieve and Co-segment for Zero-shot Transfer-
TTD (TCL)27.0TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
COSMOS ViT-B/1634.7COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
ProxyCLIP42.0ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
TagAlign27.5TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
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