1.4k citations · 2k across the 12 of their papers we have counts for
13 papers
Contrastive Multimodal Fusion with TupleInfoNCE
Yunze Liu, Qingnan Fan, Shanghang Zhang +3
This paper proposes a method for representation learning of multimodal data using contrastive losses. A traditional approach is to contrast different modalities to learn the inform…
Product semantics translation from brain activity via adversarial learning
Pan Wang, Zhifeng Gong, Shuo Wang +5
A small change of design semantics may affect a user's satisfaction with a product. To modify a design semantic of a given product from personalised brain activity via adversarial…
Generative Creativity: Adversarial Learning for Bionic Design
Simiao Yu, Hao Dong, Pan Wang +2
Bionic design refers to an approach of generative creativity in which a target object (e.g. a floor lamp) is designed to contain features of biological source objects (e.g. flowers…
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security
Hao Dong, Chao Wu, Zhen Wei +1
Deep learning methods can play a crucial role in anomaly detection, prediction, and supporting decision making for applications like personal health-care, pervasive body sensing, e…
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai +4
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduo…
Semantic Image Synthesis via Adversarial Learning
Hao Dong, Simiao Yu, Chao Wu +1
In this paper, we propose a way of synthesizing realistic images directly with natural language description, which has many useful applications, e.g. intelligent image manipulation…