17 citations · 59 across the 6 of their papers we have counts for
7 papers · 1 filter
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification
Xiaofang Wang, Xuehan Xiong, Maxim Neumann +5
Convolutional operations have two limitations: (1) do not explicitly model where to focus as the same filter is applied to all the positions, and (2) are unsuitable for modeling lo…
Point in, Box out: Beyond Counting Persons in Crowds
Yuting Liu, Miaojing Shi, Qijun Zhao +1
Modern crowd counting methods usually employ deep neural networks (DNN) to estimate crowd counts via density regression. Despite their significant improvements, the regression-base…
Learnable Embedding Space for Efficient Neural Architecture Compression
Shengcao Cao, Xiaofang Wang, Kris M. Kitani
We propose a method to incrementally learn an embedding space over the domain of network architectures, to enable the careful selection of architectures for evaluation during compr…
Error Correction Maximization for Deep Image Hashing
Xiang Xu, Xiaofang Wang, Kris M. Kitani
We propose to use the concept of the Hamming bound to derive the optimal criteria for learning hash codes with a deep network. In particular, when the number of binary hash codes (…
Image Registration Based Flicker Solving in Video Face Replacement and Analysis Based Sub-pixel Image Registration
Xiaofang Wang, Guoqiang Xiang, Xinyue Zhang +1
In this paper, a framework of video face replacement is proposed and it deals with the flicker of swapped face in video sequence. This framework contains two main innovations: 1) t…
Discriminative and Geometry Aware Unsupervised Domain Adaptation
Lingkun Luo, Liming Chen, Shiqiang Hu +2
Domain adaptation (DA) aims to generalize a learning model across training and testing data despite the mismatch of their data distributions. In light of a theoretical estimation o…