A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities

Y Song, T Wang, P Cai, SK Mondal… - ACM Computing Surveys, 2023 - dl.acm.org
Few-shot learning (FSL) has emerged as an effective learning method and shows great
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …

From show to tell: A survey on deep learning-based image captioning

M Stefanini, M Cornia, L Baraldi… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …

What does a platypus look like? generating customized prompts for zero-shot image classification

S Pratt, I Covert, R Liu… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Open-vocabulary models are a promising new paradigm for image classification. Unlike
traditional classification models, open-vocabulary models classify among any arbitrary set of …

Holistic evaluation of text-to-image models

T Lee, M Yasunaga, C Meng, Y Mai… - Advances in …, 2024 - proceedings.neurips.cc
The stunning qualitative improvement of text-to-image models has led to their widespread
attention and adoption. However, we lack a comprehensive quantitative understanding of …

Magicbrush: A manually annotated dataset for instruction-guided image editing

K Zhang, L Mo, W Chen, H Sun… - Advances in Neural …, 2024 - proceedings.neurips.cc
Text-guided image editing is widely needed in daily life, ranging from personal use to
professional applications such as Photoshop. However, existing methods are either zero …

Detclip: Dictionary-enriched visual-concept paralleled pre-training for open-world detection

L Yao, J Han, Y Wen, X Liang, D Xu… - Advances in …, 2022 - proceedings.neurips.cc
Open-world object detection, as a more general and challenging goal, aims to recognize
and localize objects described by arbitrary category names. The recent work GLIP …

Fine-grained image analysis with deep learning: A survey

XS Wei, YZ Song, O Mac Aodha, J Wu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …

Knowledge-guided semantic transfer network for few-shot image recognition

Z Li, H Tang, Z Peng, GJ Qi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning-based models have been shown to outperform human beings in many
computer vision tasks with massive available labeled training data in learning. However …

Contrastive embedding for generalized zero-shot learning

Z Han, Z Fu, S Chen, J Yang - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
Generalized zero-shot learning (GZSL) aims to recognize objects from both seen and
unseen classes, when only the labeled examples from seen classes are provided. Recent …

Free: Feature refinement for generalized zero-shot learning

S Chen, W Wang, B Xia, Q Peng… - Proceedings of the …, 2021 - openaccess.thecvf.com
Generalized zero-shot learning (GZSL) has achieved significant progress, with many efforts
dedicated to overcoming the problems of visual-semantic domain gaps and seen-unseen …