5 citations · 19 across the 10 of their papers we have counts for
10 papers
DCP-NAS: Discrepant Child-Parent Neural Architecture Search for 1-bit CNNs
Yanjing Li, Sheng Xu, Xianbin Cao +4
Neural architecture search (NAS) proves to be among the effective approaches for many tasks by generating an application-adaptive neural architecture, which is still challenged by…
DiffHand: End-to-End Hand Mesh Reconstruction via Diffusion Models
Lijun Li, Li'an Zhuo, Bang Zhang +2
Hand mesh reconstruction from the monocular image is a challenging task due to its depth ambiguity and severe occlusion, there remains a non-unique mapping between the monocular im…
One-stage Action Detection Transformer
Lijun Li, Li'an Zhuo, Bang Zhang
In this work, we introduce our solution to the EPIC-KITCHENS-100 2022 Action Detection challenge. One-stage Action Detection Transformer (OADT) is proposed to model the temporal co…
Cogradient Descent for Dependable Learning
Runqi Wang, Baochang Zhang, Li'an Zhuo +2
Conventional gradient descent methods compute the gradients for multiple variables through the partial derivative. Treating the coupled variables independently while ignoring the i…
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…
Binarized Neural Architecture Search for Efficient Object Recognition
Hanlin Chen, Li'an Zhuo, Baochang Zhang +5
Traditional neural architecture search (NAS) has a significant impact in computer vision by automatically designing network architectures for various tasks. In this paper, binarize…
Cogradient Descent for Bilinear Optimization
Li'an Zhuo, Baochang Zhang, Linlin Yang +5
Conventional learning methods simplify the bilinear model by regarding two intrinsically coupled factors independently, which degrades the optimization procedure. One reason lies i…
CP-NAS: Child-Parent Neural Architecture Search for Binary Neural Networks
Li'an Zhuo, Baochang Zhang, Hanlin Chen +4
Neural architecture search (NAS) proves to be among the best approaches for many tasks by generating an application-adaptive neural architecture, which is still challenged by high…
Binarized Neural Architecture Search
Hanlin Chen, Li'an Zhuo, Baochang Zhang +4
Neural architecture search (NAS) can have a significant impact in computer vision by automatically designing optimal neural network architectures for various tasks. A variant, bina…
The Structure Transfer Machine Theory and Applications
Baochang Zhang, Lian Zhuo, Ze Wang +2
Representation learning is a fundamental but challenging problem, especially when the distribution of data is unknown. We propose a new representation learning method, termed Struc…