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 ...
Compositional Zero-Shot Learning (CZSL) aims to recognize novel compositions using knowledge learned from seen attribute-object compositions in the training set. Previous works mainly project an image and a composition into a common embedding space to measure their compatibility score. However, both ...
Distilled Reverse Attention Network for Open-world Compositional Zero-ShotLearningYun LiUniversity of New South WalesInstitution1 addressyun.li5@unsw.edu.auZhe LiuJiangnan Universityzheliu912@gmail.comSaurav JhaUniversity of New South Walessaurav.jha@unsw.edu.auSally CrippsUniversity of Technology Sydney...
we demonstrate that representations that focus on compositionality and locality are better at zero-shot generalization. Considering how to apply these notions in practice to improve zero-shot learning performance, we also introduce Class-Matching DIM (CMDIM), a variant of the popular unsupervised l...
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 ...
Compositional zero-shot learning (CZSL) strives to learn attributes and objects from seen compositions and transfer the acquired knowledge to unseen compositions. Existing methods either learn primitive concepts in an entangled manner, leading to the model relying on spurious correlations between attribute...
Compositional Zero-Shot Learning (CZSL) is a particular Zero-Shot Learning (ZSL) task that aims to utilize known concepts (e.g., states and objects) to identify novel state-object compositions for Image Classification. Previous works have primarily focused on disentangling concept compositions or ...
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. Reference Paper:Learning to Compose Soft Prompts for Compositional Zero-S...
CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning [WACV 2024] CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning Zhaoheng Zheng, Haidong Zhu and Ram Nevatia Official implementation of CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zer...
Zero-Shot Learning—A Comprehensive Eval- uation of the Good, the Bad and the Ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019. [67] Yongqin Xian, Bernt Schiele, and Zeynep Akata. Zero-Shot Learning — The Good, the Bad and the Ug...