414 citations · 1.1k across the 31 of their papers we have counts for
7 papers · 1 filter
Dual Attention GANs for Semantic Image Synthesis
Hao Tang, Song Bai, Nicu Sebe
In this paper, we focus on the semantic image synthesis task that aims at transferring semantic label maps to photo-realistic images. Existing methods lack effective semantic const…
Bipartite Graph Reasoning GANs for Person Image Generation
Hao Tang, Song Bai, Philip H. S. Torr +1
We present a novel Bipartite Graph Reasoning GAN (BiGraphGAN) for the challenging person image generation task. The proposed graph generator mainly consists of two novel blocks tha…
Dual In-painting Model for Unsupervised Gaze Correction and Animation in the Wild
Jichao Zhang, Jingjing Chen, Hao Tang +4
In this paper we address the problem of unsupervised gaze correction in the wild, presenting a solution that works without the need for precise annotations of the gaze angle and th…
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…
XingGAN for Person Image Generation
Hao Tang, Song Bai, Li Zhang +2
We propose a novel Generative Adversarial Network (XingGAN or CrossingGAN) for person image generation tasks, i.e., translating the pose of a given person to a desired one. The pro…
When Dictionary Learning Meets Deep Learning: Deep Dictionary Learning and Coding Network for Image Recognition with Limited Data
Hao Tang, Hong Liu, Wei Xiao +1
We present a new Deep Dictionary Learning and Coding Network (DDLCN) for image recognition tasks with limited data. The proposed DDLCN has most of the standard deep learning layers…
Relevant Region Prediction for Crowd Counting
Xinya Chen, Yanrui Bin, Changxin Gao +2
Crowd counting is a concerned and challenging task in computer vision. Existing density map based methods excessively focus on the individuals' localization which harms the crowd c…