36 citations · 96 across the 10 of their papers we have counts for
10 papers
ViDA-MAN: Visual Dialog with Digital Humans
Tong Shen, Jiawei Zuo, Fan Shi +7
We demonstrate ViDA-MAN, a digital-human agent for multi-modal interaction, which offers realtime audio-visual responses to instant speech inquiries. Compared to traditional text o…
Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis
Tong Sha, Wei Zhang, Tong Shen +2
Deep person generation has attracted extensive research attention due to its wide applications in virtual agents, video conferencing, online shopping and art/movie production. With…
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
Haoran Wang, Tong Shen, Wei Zhang +2
Despite great progress in supervised semantic segmentation,a large performance drop is usually observed when deploying the model in the wild. Domain adaptation methods tackle the i…
Zooming into Face Forensics: A Pixel-level Analysis
Jia Li, Tong Shen, Wei Zhang +3
The stunning progress in face manipulation methods has made it possible to synthesize realistic fake face images, which poses potential threats to our society. It is urgent to have…
Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
Tong Shen, Dong Gong, Wei Zhang +2
Training a semantic segmentation model requires a large amount of pixel-level annotation, hampering its application at scale. With computer graphics, we can generate almost unlimit…
Everyone is a Cartoonist: Selfie Cartoonization with Attentive Adversarial Networks
Xinyu Li, Wei Zhang, Tong Shen +1
Selfie and cartoon are two popular artistic forms that are widely presented in our daily life. Despite the great progress in image translation/stylization, few techniques focus spe…
Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation
Tianyi Zhang, Guosheng Lin, Jianfei Cai +3
Weakly supervised semantic segmentation receives much research attention since it alleviates the need to obtain a large amount of dense pixel-wise ground-truth annotations for the…
Semantic Segmentation from Limited Training Data
A. Milan, T. Pham, K. Vijay +22
We present our approach for robotic perception in cluttered scenes that led to winning the recent Amazon Robotics Challenge (ARC) 2017. Next to small objects with shiny and transpa…
Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation
Tong Shen, Guosheng Lin, Lingqiao Liu +2
Training a Fully Convolutional Network (FCN) for semantic segmentation requires a large number of masks with pixel level labelling, which involves a large amount of human labour an…
Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation
Tong Shen, Guosheng Lin, Chunhua Shen +1
Semantic image segmentation is a fundamental task in image understanding. Per-pixel semantic labelling of an image benefits greatly from the ability to consider region consistency…