26 citations · 51 across the 9 of their papers we have counts for
9 papers · 1 filter
Cross-View Panorama Image Synthesis
Songsong Wu, Hao Tang, Xiao-Yuan Jing +4
In this paper, we tackle the problem of synthesizing a ground-view panorama image conditioned on a top-view aerial image, which is a challenging problem due to the large gap betwee…
DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
Ming Tao, Hao Tang, Fei Wu +3
Synthesizing high-quality realistic images from text descriptions is a challenging task. Existing text-to-image Generative Adversarial Networks generally employ a stacked architect…
Cross-View Image Synthesis with Deformable Convolution and Attention Mechanism
Hao Ding, Songsong Wu, Hao Tang +3
Learning to generate natural scenes has always been a daunting task in computer vision. This is even more laborious when generating images with very different views. When the views…
Modal Regression based Structured Low-rank Matrix Recovery for Multi-view Learning
Jiamiao Xu, Fangzhao Wang, Qinmu Peng +4
Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods…
Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering
Songsong Wu, Zhiqiang Lu, Hao Tang +4
Multi-view subspace clustering aims to divide a set of multisource data into several groups according to their underlying subspace structure. Although the spectral clustering based…
Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation
Songsong Wu, Yan Yan, Hao Tang +3
Unsupervised Domain Adaptation (UDA) addresses the problem of performance degradation due to domain shift between training and testing sets, which is common in computer vision appl…
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling
Peng Zhang, Shujian Yu, Jiamiao Xu +4
It remains a huge challenge to design effective and efficient trackers under complex scenarios, including occlusions, illumination changes and pose variations. To cope with this pr…
Multi-view Common Component Discriminant Analysis for Cross-view Classification
Xinge You, Jiamiao Xu, Wei Yuan +3
Cross-view classification that means to classify samples from heterogeneous views is a significant yet challenging problem in computer vision. A promising approach to handle this p…
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach
Jiamiao Xu, Shujian Yu, Xinge You +3
We present a novel cross-view classification algorithm where the gallery and probe data come from different views. A popular approach to tackle this problem is the multi-view subsp…