Compositional reasoning是智能体的特点,学习一种从简单到困难的组合方式,比如我们学紫色,红色,西兰花等这些特征,然后希望我们的model能够重新组合这些简单特征从而解决新问题。 zero-shot给是组合推理的限定词,表示我们的测试数据是完全没有出现在训练数据里面的。 将要识别的物体分为attribute-object pair,那么问题定义如...
内容提示: Learning Attention Propagation for Compositional Zero-Shot LearningMuhammad Gul Zain Ali Khan 1,3,4 Muhammad Ferjad Naeem 2 Luc Van Gool 2A. Pagani 1,3 Didier Stricker 1,3,4 Muhammad Zeshan Afzal 1,3,41 DFKI, 2 ETH Zürich, 3 TU Kaiserslautern, 4 MindGarageAbstractCompositional ...
In this paper, we study the problem of recognizing compositional attribute-object concepts within the zero-shot learning (ZSL) framework. We propose an episode-based cross-attention (EpiCA) network which combines merits of cross-attention mechanism and episode-based training strategy to recognize novel...
Compositional Zero-Shot Learning (CZSL) aims to transfer knowledge from seen state-object pairs to novel unseen pairs. In this process, visual bias caused by the diverse interrelationship of state-object combinations blurs their visual features, hindering the learning of distinguishable class prototypes...
Zero-shot learning from scratch To tie this all together to generalization, we evaluate each of these models on the downstream task of zero-shot learning. However, because state-of-the-art ZSL in computer vision also relies heavily on pre-training from large-scale datasets like ImageNet...
In-context Learning(上下文学习) Zero-shot: 如果将一个机器翻译的任务告诉大语言模型,要从英语翻译成法语,然后给一个英语词汇 One-shot: 除了给任务,还给一个例子 大语言模型除了有了任务本身的理解,还多了一个从输入到输出的映射格式 Few-shot: 给多个例子 ...
BSD-3-Clause license Compositional Soft Prompting (CSP) Compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositionality of large-scale pretrained vision-language models (VLMs) without the overhead of fine-tuning the entire model. ...
LVAR-CZSL: Learning Visual Attributes Representation for Compositional Zero-Shot Learning - mxjmxj1/LVAR-CZSL
In compositional zero-shot learning, the goal is to recognize unseen compositions (e.g. old dog) of observed visual primitives states (e.g. old, cute) and objects (e.g. car, dog) in the training set. This is challenging because the same state can for example alter the visual appearance...
To facilitate the research on language-guided agents with domain adaption, we propose a novel zero-shot compositional policy learning task, where the environments are characterized as a composition of different attributes. Since there are no public environments supporting this study, we introduce a ...