103 citations · 623 across the 53 of their papers we have counts for
7 papers · 1 filter
Amalgamating Knowledge towards Comprehensive Classification
Chengchao Shen, Xinchao Wang, Jie Song +2
With the rapid development of deep learning, there have been an unprecedentedly large number of trained deep network models available online. Reusing such trained models can signif…
Selective Zero-Shot Classification with Augmented Attributes
Jie Song, Chengchao Shen, Jie Lei +4
In this paper, we introduce a selective zero-shot classification problem: how can the classifier avoid making dubious predictions? Existing attribute-based zero-shot classification…
Interpretable Partitioned Embedding for Customized Fashion Outfit Composition
Zunlei Feng, Zhenyun Yu, Yezhou Yang +3
Intelligent fashion outfit composition becomes more and more popular in these years. Some deep learning based approaches reveal competitive composition recently. However, the unexp…
Dual Swap Disentangling
Zunlei Feng, Xinchao Wang, Chenglong Ke +3
Learning interpretable disentangled representations is a crucial yet challenging task. In this paper, we propose a weakly semi-supervised method, termed as Dual Swap Disentangling…
Transductive Unbiased Embedding for Zero-Shot Learning
Jie Song, Chengchao Shen, Yezhou Yang +2
Most existing Zero-Shot Learning (ZSL) methods have the strong bias problem, in which instances of unseen (target) classes tend to be categorized as one of the seen (source) classe…
Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields
Yongcheng Jing, Yang Liu, Yezhou Yang +4
The Fast Style Transfer methods have been recently proposed to transfer a photograph to an artistic style in real-time. This task involves controlling the stroke size in the styliz…