45 citations · 270 across the 21 of their papers we have counts for
10 papers · 1 filter
Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN
Guoping Zhao, Mingyu Zhang, Jiajun Liu +1
Studies show that Deep Neural Network (DNN)-based image classification models are vulnerable to maliciously constructed adversarial examples. However, little effort has been made t…
Face-Focused Cross-Stream Network for Deception Detection in Videos
Mingyu Ding, An Zhao, Zhiwu Lu +2
Automated deception detection (ADD) from real-life videos is a challenging task. It specifically needs to address two problems: (1) Both face and body contain useful cues regarding…
Zero-Shot Learning with Sparse Attribute Propagation
Nanyi Fei, Jiechao Guan, Zhiwu Lu +2
Zero-shot learning (ZSL) aims to recognize a set of unseen classes without any training images. The standard approach to ZSL requires a set of training images annotated with seen c…
Recursive Visual Attention in Visual Dialog
Yulei Niu, Hanwang Zhang, Manli Zhang +3
Visual dialog is a challenging vision-language task, which requires the agent to answer multi-round questions about an image. It typically needs to address two major problems: (1)…
Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning
Zhiwu Lu, Jiechao Guan, Aoxue Li +3
Zero-shot learning (ZSL) is made possible by learning a projection function between a feature space and a semantic space (e.g.,~an attribute space). Key to ZSL is thus to learn a p…
Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning
Aoxue Li, Zhiwu Lu, Jiechao Guan +3
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to unseen ones so that the latter can be recognised without any training samples. This is made possible by lea…
Domain-Invariant Projection Learning for Zero-Shot Recognition
An Zhao, Mingyu Ding, Jiechao Guan +3
Zero-shot learning (ZSL) aims to recognize unseen object classes without any training samples, which can be regarded as a form of transfer learning from seen classes to unseen ones…
Multi-Modal Multi-Scale Deep Learning for Large-Scale Image Annotation
Yulei Niu, Zhiwu Lu, Ji-Rong Wen +2
Image annotation aims to annotate a given image with a variable number of class labels corresponding to diverse visual concepts. In this paper, we address two main issues in large-…
Zero-Shot Fine-Grained Classification by Deep Feature Learning with Semantics
Aoxue Li, Zhiwu Lu, Liwei Wang +3
Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task due to two main issues: lack of sufficient training data for eve…
Image classification by visual bag-of-words refinement and reduction
Zhiwu Lu, Liwei Wang, Ji-Rong Wen
This paper presents a new framework for visual bag-of-words (BOW) refinement and reduction to overcome the drawbacks associated with the visual BOW model which has been widely used…