138 citations · 294 across the 13 of their papers we have counts for
9 papers · 1 filter
Multi-Objective Evolutionary for Object Detection Mobile Architectures Search
Haichao Zhang, Jiashi Li, Xin Xia +2
Recently, Neural architecture search has achieved great success on classification tasks for mobile devices. The backbone network for object detection is usually obtained on the ima…
Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Jiashi Li, Xin Xia, Wei Li +6
Due to the complex attention mechanisms and model design, most existing vision Transformers (ViTs) can not perform as efficiently as convolutional neural networks (CNNs) in realist…
MoCoViT: Mobile Convolutional Vision Transformer
Hailong Ma, Xin Xia, Xing Wang +3
Recently, Transformer networks have achieved impressive results on a variety of vision tasks. However, most of them are computationally expensive and not suitable for real-world mo…
TRT-ViT: TensorRT-oriented Vision Transformer
Xin Xia, Jiashi Li, Jie Wu +4
We revisit the existing excellent Transformers from the perspective of practical application. Most of them are not even as efficient as the basic ResNets series and deviate from th…
SepViT: Separable Vision Transformer
Wei Li, Xing Wang, Xin Xia +5
Vision Transformers have witnessed prevailing success in a series of vision tasks. However, these Transformers often rely on extensive computational costs to achieve high performan…
Deformable Gabor Feature Networks for Biomedical Image Classification
Xuan Gong, Xin Xia, Wentao Zhu +3
In recent years, deep learning has dominated progress in the field of medical image analysis. We find however, that the ability of current deep learning approaches to represent the…
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
Xin Xia, Xuefeng Xiao, Xing Wang +1
Neural Architecture Search (NAS) has attracted growing interest. To reduce the search cost, recent work has explored weight sharing across models and made major progress in One-Sho…
Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation
Chunlei Liu, Wenrui Ding, Xin Xia +5
The rapidly decreasing computation and memory cost has recently driven the success of many applications in the field of deep learning. Practical applications of deep learning in re…
RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs
Chunlei Liu, Wenrui Ding, Xin Xia +5
Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips b…