activity
20172022
most citedNetwork Sketching: Exploiting Binary Structure in Deep CNNs

13 citations · 26 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2022

SC-wLS: Towards Interpretable Feed-forward Camera Re-localization

Xin Wu, Hao Zhao, Shunkai Li +2

Visual re-localization aims to recover camera poses in a known environment, which is vital for applications like robotics or augmented reality. Feed-forward absolute camera pose re…

cs.CV20213 cited

Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck

Liyi Luo, Beiwen Tian, Hao Zhao +1

Semantic understanding of 3D point clouds is important for various robotics applications. Given that point-wise semantic annotation is expensive, in this paper, we address the chal…

cs.CV2020

LID 2020: The Learning from Imperfect Data Challenge Results

Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32

Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…

cs.CV20196 cited

Efficient Semantic Scene Completion Network with Spatial Group Convolution

Jiahui Zhang, Hao Zhao, Anbang Yao +3

We introduce Spatial Group Convolution (SGC) for accelerating the computation of 3D dense prediction tasks. SGC is orthogonal to group convolution, which works on spatial dimension…

cs.CV2019

Deeply-supervised Knowledge Synergy

Dawei Sun, Anbang Yao, Aojun Zhou +1

Convolutional Neural Networks (CNNs) have become deeper and more complicated compared with the pioneering AlexNet. However, current prevailing training scheme follows the previous…

cs.CV2019

A Closed-form Solution to Universal Style Transfer

Ming Lu, Hao Zhao, Anbang Yao +3

Universal style transfer tries to explicitly minimize the losses in feature space, thus it does not require training on any pre-defined styles. It usually uses different layers of…