activity
20192022
most citedStructured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation

2 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Deep Unsupervised Key Frame Extraction for Efficient Video Classification

Hao Tang, Lei Ding, Songsong Wu +3

Video processing and analysis have become an urgent task since a huge amount of videos (e.g., Youtube, Hulu) are uploaded online every day. The extraction of representative key fra…

cs.CV2022

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…

cs.CV20201 cited

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…

cs.CV2019

Expression Conditional GAN for Facial Expression-to-Expression Translation

Hao Tang, Wei Wang, Songsong Wu +4

In this paper, we focus on the facial expression translation task and propose a novel Expression Conditional GAN (ECGAN) which can learn the mapping from one image domain to anothe…

cs.CV2019

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…

cs.CV20192 cited

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…