36 citations · 100 across the 15 of their papers we have counts for
5 papers · 1 filter
Domain Generalization via Balancing Training Difficulty and Model Capability
Xueying Jiang, Jiaxing Huang, Sheng Jin +1
Domain generalization (DG) aims to learn domain-generalizable models from one or multiple source domains that can perform well in unseen target domains. Despite its recent progress…
GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition
Ruijie Yao, Sheng Jin, Lumin Xu +5
Multi-Label Image Recognition (MLIR) is a challenging task that aims to predict multiple object labels in a single image while modeling the complex relationships between labels and…
Prompt Ensemble Self-training for Open-Vocabulary Domain Adaptation
Jiaxing Huang, Jingyi Zhang, Han Qiu +2
Traditional domain adaptation assumes the same vocabulary across source and target domains, which often struggles with limited transfer flexibility and efficiency while handling ta…
Vision-Language Models for Vision Tasks: A Survey
Jingyi Zhang, Jiaxing Huang, Sheng Jin +1
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, l…
Aligning Bag of Regions for Open-Vocabulary Object Detection
Size Wu, Wenwei Zhang, Sheng Jin +2
Pre-trained vision-language models (VLMs) learn to align vision and language representations on large-scale datasets, where each image-text pair usually contains a bag of semantic…