HyperAI

Open Vocabulary Semantic Segmentation On 1

Métriques

mIoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
mIoU
Paper TitleRepository
TCL33.9Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs
PACL50.1Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning
TaAlign(trained with image-text pairs)37.6TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
Mask-Adapter60.4Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation-
FC-CLIP58.4Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
MAFT+59.4Collaborative Vision-Text Representation Optimizing for Open-Vocabulary Segmentation
MAFT-ViTL58.5Learning Mask-aware CLIP Representations for Zero-Shot Segmentation-
CAT-Seg63.3CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
OVSeg Swin-B55.7Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP
SED60.6SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation
LaVG34.7In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation
HyperSeg64.6HyperSeg: Towards Universal Visual Segmentation with Large Language Model
TTD (TCL)37.4TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
SimSeg47.7A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model
SILC63.5SILC: Improving Vision Language Pretraining with Self-Distillation-
MaskCLIP45.9Open-Vocabulary Universal Image Segmentation with MaskCLIP
EBSeg-L60.2Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
CLIP Surgery (original CLIP without any fine-tuning)29.3A Closer Look at the Explainability of Contrastive Language-Image Pre-training
MaskCLIP++62.5MaskCLIP++: A Mask-Based CLIP Fine-tuning Framework for Open-Vocabulary Image Segmentation
SCAN59.3Open-Vocabulary Segmentation with Semantic-Assisted Calibration
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