7 code implementations • NeurIPS 2020 • Zi-Hang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan
The novel convolution heads, together with the rest self-attention heads, form a new mixed attention block that is more efficient at both global and local context learning.
2 code implementations • 22 Mar 2019 • Xiaoguang Tu, Jian Zhao, Zi-Hang Jiang, Yao Luo, Mei Xie, Yang Zhao, Linxiao He, Zheng Ma, Jiashi Feng
3D face reconstruction from a single 2D image is a challenging problem with broad applications.
Ranked #7 on Face Alignment on AFLW2000-3D
1 code implementation • CVPR 2019 • Zi-Hang Jiang, Qianyi Wu, Keyu Chen, Juyong Zhang
In this paper, we present a novel strategy to design disentangled 3D face shape representation.
1 code implementation • ICLR 2020 • Weihao Yu, Zi-Hang Jiang, Yanfei Dong, Jiashi Feng
Empirical results show that state-of-the-art models have an outstanding ability to capture biases contained in the dataset with high accuracy on EASY set.
Ranked #1 on Logical Reasoning Question Answering on ReClor
1 code implementation • 6 Aug 2020 • Zi-Hang Jiang, Bingyi Kang, Kuangqi Zhou, Jiashi Feng
To be specific, we devise a simple and efficient meta-reweighting strategy to adapt the sample representations and generate soft attention to refine the representation such that the relevant features from the query and support samples can be extracted for a better few-shot classification.