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Found 4 papers, 4 papers with code
Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation
However, existing approaches often rely on impractical supervised pre-training or access to additional pre-trained networks.
A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models
Efficient transfer learning (ETL) is receiving increasing attention to adapt large pre-trained language-vision models on downstream tasks with a few labeled samples.
A Strong Baseline for Generalized Few-Shot Semantic Segmentation
In addition, the terms derived from our MI-based formulation are coupled with a knowledge distillation term to retain the knowledge on base classes.
Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE
We address this problem by proposing a framework capable of disentangling class-related and class-independent factors of variation in data.
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