92 citations · 112 across the 12 of their papers we have counts for
8 papers · 1 filter
Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP
Qi Qian, Yuanhong Xu, Juhua Hu
Vision-language pre-training methods, e.g., CLIP, demonstrate an impressive zero-shot performance on visual categorizations with the class proxy from the text embedding of the clas…
AugDMC: Data Augmentation Guided Deep Multiple Clustering
Jiawei Yao, Enbei Liu, Maham Rashid +1
Clustering aims to group similar objects together while separating dissimilar ones apart. Thereafter, structures hidden in data can be identified to help understand data in an unsu…
Improved Visual Fine-tuning with Natural Language Supervision
Junyang Wang, Yuanhong Xu, Juhua Hu +3
Fine-tuning a visual pre-trained model can leverage the semantic information from large-scale pre-training data and mitigate the over-fitting problem on downstream vision tasks wit…
Unsupervised Visual Representation Learning by Online Constrained K-Means
Qi Qian, Yuanhong Xu, Juhua Hu +2
Cluster discrimination is an effective pretext task for unsupervised representation learning, which often consists of two phases: clustering and discrimination. Clustering is to as…
Weakly Supervised Representation Learning with Coarse Labels
Yuanhong Xu, Qi Qian, Hao Li +2
With the development of computational power and techniques for data collection, deep learning demonstrates a superior performance over most existing algorithms on visual benchmark…
Hierarchically Robust Representation Learning
Qi Qian, Juhua Hu, Hao Li
With the tremendous success of deep learning in visual tasks, the representations extracted from intermediate layers of learned models, that is, deep features, attract much attenti…
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
Qi Qian, Lei Shang, Baigui Sun +3
Distance metric learning (DML) is to learn the embeddings where examples from the same class are closer than examples from different classes. It can be cast as an optimization prob…
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
Lingyang Chu, Xia Hu, Juhua Hu +2
Strong intelligent machines powered by deep neural networks are increasingly deployed as black boxes to make decisions in risk-sensitive domains, such as finance and medical. To re…