37 citations · 47 across the 5 of their papers we have counts for
5 papers
Weak Novel Categories without Tears: A Survey on Weak-Shot Learning
Li Niu
Deep learning is a data-hungry approach, which requires massive training data. However, it is time-consuming and labor-intensive to collect abundant fully-annotated training data f…
Fine-grained Classification using Heterogeneous Web Data and Auxiliary Categories
Li Niu, Ashok Veeraraghavan, Ashu Sabharwal
Fine-grained classification remains a very challenging problem, because of the absence of well-labeled training data caused by the high cost of annotating a large number of fine-gr…
Learning from Noisy Web Data with Category-level Supervision
Li Niu, Qingtao Tang, Ashok Veeraraghavan +1
As tons of photos are being uploaded to public websites (e.g., Flickr, Bing, and Google) every day, learning from web data has become an increasingly popular research direction bec…
Zero-Shot Learning via Category-Specific Visual-Semantic Mapping
Li Niu, Jianfei Cai, Ashok Veeraraghavan
Zero-Shot Learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories, in which the gap between seen categories and…
Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models
Jiuxiang Gu, Jianfei Cai, Shafiq Joty +2
Textual-visual cross-modal retrieval has been a hot research topic in both computer vision and natural language processing communities. Learning appropriate representations for mul…