175 citations · 634 across the 52 of their papers we have counts for
5 papers · 1 filter
Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification
Xiu-Shen Wei, Chen-Lin Zhang, Lingqiao Liu +2
Vehicle re-identification is an important problem and becomes desirable with the rapid expansion of applications in video surveillance and intelligent transportation. By recalling…
Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation
Bohan Zhuang, Chunhua Shen, Mingkui Tan +2
In this paper, we propose to train convolutional neural networks (CNNs) with both binarized weights and activations, leading to quantized models specifically} for mobile devices wi…
Towards Effective Deep Embedding for Zero-Shot Learning
Lei Zhang, Peng Wang, Lingqiao Liu +4
Zero-shot learning (ZSL) can be formulated as a cross-domain matching problem: after being projected into a joint embedding space, a visual sample will match against all candidate…
Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network
Lei Zhang, Peng Wang, Chunhua Shen +4
Deep neural networks have achieved remarkable success in single image super-resolution (SISR). The computing and memory requirements of these methods have hindered their applicatio…
Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples
Xiu-Shen Wei, Peng Wang, Lingqiao Liu +2
Humans are capable of learning a new fine-grained concept with very little supervision, \emph{e.g.}, few exemplary images for a species of bird, yet our best deep learning systems…