71 citations · 416 across the 50 of their papers we have counts for
8 papers · 1 filter
In Defense of Single-column Networks for Crowd Counting
Ze Wang, Zehao Xiao, Kai Xie +3
Crowd counting usually addressed by density estimation becomes an increasingly important topic in computer vision due to its widespread applications in video surveillance, urban pl…
LaneNet: Real-Time Lane Detection Networks for Autonomous Driving
Ze Wang, Weiqiang Ren, Qiang Qiu
Lane detection is to detect lanes on the road and provide the accurate location and shape of each lane. It severs as one of the key techniques to enable modern assisted and autonom…
Learning to Collaborate for User-Controlled Privacy
Martin Bertran, Natalia Martinez, Afroditi Papadaki +3
It is becoming increasingly clear that users should own and control their data. Utility providers are also becoming more interested in guaranteeing data privacy. As such, users and…
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks
Xiuyuan Cheng, Qiang Qiu, Robert Calderbank +1
Explicit encoding of group actions in deep features makes it possible for convolutional neural networks (CNNs) to handle global deformations of images, which is critical to success…
Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning
Wei Zhu, Qiang Qiu, Bao Wang +3
Deep neural networks (DNNs) typically have enough capacity to fit random data by brute force even when conventional data-dependent regularizations focusing on the geometry of the f…
Weakly Supervised Instance Segmentation using Class Peak Response
Yanzhao Zhou, Yi Zhu, Qixiang Ye +2
Weakly supervised instance segmentation with image-level labels, instead of expensive pixel-level masks, remains unexplored. In this paper, we tackle this challenging problem by ex…
Virtual CNN Branching: Efficient Feature Ensemble for Person Re-Identification
Albert Gong, Qiang Qiu, Guillermo Sapiro
In this paper we introduce an ensemble method for convolutional neural network (CNN), called "virtual branching," which can be implemented with nearly no additional parameters and…
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Qiang Qiu, Xiuyuan Cheng, Robert Calderbank +1
Filters in a Convolutional Neural Network (CNN) contain model parameters learned from enormous amounts of data. In this paper, we suggest to decompose convolutional filters in CNN…