Results 31 to 40 of about 11,177,407 (275)

Zero-shot Image Classification [PDF]

, 2017
Image classification is one of the essential tasks for the intelligent visual system. Conventional image classification techniques rely on a large number of labelled images for supervised learning, which requires expensive human annotations. Towards real
Long, Yang
core   +2 more sources

CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets

CoRR, 2023
Accepted at ICML ...
Zachary Novack, Saurabh Garg, Julian J. McAuley, Zachary C. Lipton   +3 more
openaire   +3 more sources

Zero-Shot Recognition through Image-Guided Semantic Classification

CoRR, 2020
We present a new embedding-based framework for zero-shot learning (ZSL). Most embedding-based methods aim to learn the correspondence between an image classifier (visual representation) and its class prototype (semantic representation) for each class. Motivated by the binary relevance method for multi-label classification, we propose to inversely learn
Mei-Chen Yeh, Fang Li
openaire   +3 more sources

A Survey of Zero-Shot Image Classification: Concepts, Developments, and Challenges

Tsinghua Science and Technology
Zero-shot learning is gaining increasing attention in the social computing community, primarily because it can enable models to effectively perform classification or regression tasks when new concepts continually emerge while lacking sufficient training ...
Shuai Xu, Yue Wang, Xuelin Zhu, Donghai Guan, Ziqian Zhang, Feng Lin   +5 more
doaj   +1 more source

Method for improving zero‐shot image classification

The Journal of Engineering, 2018
In order to improve the robustness of the similarity metric method of image classification, and reduce the complexity of the measure function, the Pearson correlation coefficient is introduced to improve the zero‐shot image classification. Firstly, the mapping matrix from visual space to semantic space is learned by the training dataset, and the visual
Xiangfeng Chen, Wenbai Chen, Chong Zhang, Mengyao Lv, Hu Han   +4 more
openaire   +1 more source

Fusing MPEG-7 visual descriptors for image classification [PDF]

, 2005
This paper proposes three content-based image classification techniques based on fusing various low-level MPEG-7 visual descriptors. Fusion is necessary as descriptors would be otherwise incompatible and inappropriate to directly include e.g.
Eddie Cooke, Mailis, T, Evaggelos Spyrou, Yannis Avrithis, Avrithis, Yannis, Le Borgne, Hervé, Cooke, Eddie, Mailis, Theofilos, Borgne, HL, Cooke, E, Noel O’Connor, Hervé Le Borgne, O'Connor, N, O'Connor, Noel E., Spyrou, E, Spyrou, Evaggelos, Theofilos Mailis, Avrithis, Y, O\u27Connor, Noel E.   +18 more
core   +2 more sources

SPECIAL: Zero-Shot Hyperspectral Image Classification With CLIP

IEEE Transactions on Geoscience and Remote Sensing
Hyperspectral image (HSI) classification aims to categorize each pixel in an HSI into a specific land cover class, which is crucial for applications such as remote sensing, environmental monitoring, and agriculture. Although deep learning-based HSI classification methods have achieved significant advancements, existing methods still rely on manually ...
Li Pang, Jing Yao, Kaiyu Li, Jun Zhou, Deyu Meng, Xiangyong Cao   +5 more
openaire   +2 more sources

Open-Pose 3D zero-shot learning: Benchmark and challenges [PDF]

With the explosive 3D data growth, the urgency of utilizing zero-shot learning to facilitate data labeling becomes evident. Recently, methods transferring language or language-image pre-training models like Contrastive Language-Image Pre-training (CLIP ...
Hussain, Amir, Yan, Yuyao, Jiang, Chenru, Zhao, Weiguang, Yang, Chaolong, Zhang, Rui, Huang, Kaizhu, Yang, Guanyu   +7 more
core   +1 more source

Concept-Guided Prediction Refinement for Zero-Shot Style Classification

IEEE Access
Recent vision-language models (VLMs) have demonstrated impressive zero-shot image classification capabilities without requiring task-specific training.
Yoorim Kim, Jungyeob Han, Daeho Um
doaj   +1 more source

Learning Multimodal Latent Attributes [PDF]

, 2014
—The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via ...
Yanwei Fu, Tao Xiang, Fu, Y, Timothy M. Hospedales, Shaogang Gong, Xiang, T, Hospedales, TM, Gong, S   +7 more
core   +1 more source