A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities
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 …
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
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 …
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
Open-vocabulary models are a promising new paradigm for image classification. Unlike
traditional classification models, open-vocabulary models classify among any arbitrary set of …
traditional classification models, open-vocabulary models classify among any arbitrary set of …
Holistic evaluation of text-to-image models
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 …
attention and adoption. However, we lack a comprehensive quantitative understanding of …
Magicbrush: A manually annotated dataset for instruction-guided image editing
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 …
professional applications such as Photoshop. However, existing methods are either zero …
Detclip: Dictionary-enriched visual-concept paralleled pre-training for open-world detection
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 …
and localize objects described by arbitrary category names. The recent work GLIP …
Fine-grained image analysis with deep learning: A survey
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 …
vision and pattern recognition, and underpins a diverse set of real-world applications. The …
Knowledge-guided semantic transfer network for few-shot image recognition
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 …
computer vision tasks with massive available labeled training data in learning. However …
Contrastive embedding for generalized zero-shot learning
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 …
unseen classes, when only the labeled examples from seen classes are provided. Recent …
Free: Feature refinement for generalized zero-shot learning
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 …
dedicated to overcoming the problems of visual-semantic domain gaps and seen-unseen …