activity
20192021
most citedHierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

28 citations · 28 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Personalized Image Semantic Segmentation

Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang +2

Semantic segmentation models trained on public datasets have achieved great success in recent years. However, these models didn't consider the personalization issue of segmentation…

cs.CV2020

DEPARA: Deep Attribution Graph for Deep Knowledge Transferability

Jie Song, Yixin Chen, Jingwen Ye +4

Exploring the intrinsic interconnections between the knowledge encoded in PRe-trained Deep Neural Networks (PR-DNNs) of heterogeneous tasks sheds light on their mutual transferabil…

cs.CV2019

Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift

Da Chen, Yongliang Yang, Zunlei Feng +6

Few-shot image classification requires the classifier to robustly cope with unseen classes even if there are only a few samples for each class. Recent advances benefit from the met…

cs.CV2019

Self-Supervised Learning For Few-Shot Image Classification

Da Chen, Yuefeng Chen, Yuhong Li +3

Few-shot image classification aims to classify unseen classes with limited labelled samples. Recent works benefit from the meta-learning process with episodic tasks and can fast ad…

cs.CV201928 cited

Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

Feng Mao, Xiang Wu, Hui Xue +1

High accuracy video label prediction (classification) models are attributed to large scale data. These data could be frame feature sequences extracted by a pre-trained convolutiona…