14 citations · 29 across the 5 of their papers we have counts for
5 papers
CEKD:Cross Ensemble Knowledge Distillation for Augmented Fine-grained Data
Ke Zhang, Jin Fan, Shaoli Huang +3
Data augmentation has been proved effective in training deep models. Existing data augmentation methods tackle the fine-grained problem by blending image pairs and fusing correspon…
Structure-Aware Feature Generation for Zero-Shot Learning
Lianbo Zhang, Shaoli Huang, Xinchao Wang +2
Zero-Shot Learning (ZSL) targets at recognizing unseen categories by leveraging auxiliary information, such as attribute embedding. Despite the encouraging results achieved, prior…
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
Shaoli Huang, Xinchao Wang, Dacheng Tao
Data mixing augmentation has proved effective in training deep models. Recent methods mix labels mainly based on the mixture proportion of image pixels. As the main discriminative…
An End-to-end Framework for Unconstrained Monocular 3D Hand Pose Estimation
Sanjeev Sharma, Shaoli Huang, Dacheng Tao
This work addresses the challenging problem of unconstrained 3D hand pose estimation using monocular RGB images. Most of the existing approaches assume some prior knowledge of hand…
Not All Parts Are Created Equal: 3D Pose Estimation by Modelling Bi-directional Dependencies of Body Parts
Jue Wang, Shaoli Huang, Xinchao Wang +1
Not all the human body parts have the same~degree of freedom~(DOF) due to the physiological structure. For example, the limbs may move more flexibly and freely than the torso does.…