The Text2Model approach aims to build task-specific representations and classifiers by generating models tailored to specific classification tasks based on text descriptions. The method outperforms existing approaches in various scenarios, including images, 3D point clouds, and action recognition, showcasing its adaptability and effectiveness.
The content discusses the challenges of zero-shot image classification using text descriptions and presents a novel approach called Text2Model (T2M). T2M generates task-specific classifiers at inference time based on class descriptions, improving generalization over fixed representation methods. The approach is evaluated across different datasets and scenarios, showing superior performance compared to existing baselines.
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by Ohad Amosy,T... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2210.15182.pdfDeeper Inquiries