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Zero-shot Image Classification Method Based on Discriminator Feedback
Journal of Harbin University of Science and Technology, 2023 Zero-shot learning (ZSL) strives to classify unseen categories for which no data is available during training.At present, among generative methods, zero-shot learning based on joint generative model VAEGAN is a research hotspot.On this basis, we propose ...
FAN Yufei, DING Bo, HE Yongjun
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Multi-Label Zero-Shot Classification Based on Deep Mutual Learning [PDF]
Jisuanji gongcheng, 2023 Numerous methods have been proposed to solve the zero-shot image classification problem; however, there are limited studies on the multi-label zero-shot image classification problem. In the existing solutions, in addition to the use of the basic settings
Zhixiang YUAN, Yaqing WANG, Jun HUANG
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RS-CLIP: Zero shot remote sensing scene classification via contrastive vision-language supervision
International Journal of Applied Earth Observations and Geoinformation, 2023 Zero-shot remote sensing scene classification aims to solve the scene classification problem on unseen categories and has attracted numerous research attention in the remote sensing field.
Xiang Li +3 more
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Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos [PDF]
, 2010 In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection.
Chen, J., Jiang, J., Ren, Jinchang
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Domain-Aware Continual Zero-Shot Learning
, 2021 We introduce Domain Aware Continual Zero-Shot Learning (DACZSL), the task of visually recognizing images of unseen categories in unseen domains sequentially. We created DACZSL on top of the DomainNet dataset by dividing it into a sequence of tasks, where
Yi, Kai
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I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification
Advances in Neural Information Processing Systems 35, 2022 ISBN:978-1-7138-7108 ...
Naeem, Muhammad Ferjad; id_orcid0000-0001-7455-7280 +3 more
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Transductive Multi-View Zero-Shot Learning [PDF]
, 2015 (c) 2012. The copyright of this document resides with its authors.
Yanwei Fu +8 more
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A decadal survey of zero-shot image classification [PDF]
SCIENTIA SINICA Informationis, 2019 Zero-shot image classification refers to learning a visual classifier for categories with zero training examples. This method can effectively solve problems in which the labeled data for some classes are absent and has therefore gained a considerable attention recently. It has been approximately a decade since this technology was first developed.
Yanwei PANG +3 more
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Broad Attribute Prediction Model With Enhanced Attribute and Feature
IEEE Access, 2019 For the zero-shot image classification without intersection between training and testing sets, the high-quality representation of image attributes and features plays a key role to improve the classification performance.
Jiarui Zhang, Xuesong Wang, Yuhu Cheng
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Zero-Shot Visual Classification with Guided Cropping [PDF]
, 2023 Pretrained vision-language models, such as CLIP, show promising zero-shot performance across a wide variety of datasets. For closed-set classification tasks, however, there is an inherent limitation: CLIP image encoders are typically designed to extract ...
Saranrittichai, Piyapat +3 more
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