379 citations · 527 across the 6 of their papers we have counts for
6 papers
Understanding Convolution for Semantic Segmentation
Panqu Wang, Pengfei Chen, Ye Yuan +4
Recent advances in deep learning, especially deep convolutional neural networks (CNNs), have led to significant improvement over previous semantic segmentation systems. Here we sho…
Demystifying Neural Style Transfer
Yanghao Li, Naiyan Wang, Jiaying Liu +1
Neural Style Transfer has recently demonstrated very exciting results which catches eyes in both academia and industry. Despite the amazing results, the principle of neural style t…
Factorized Bilinear Models for Image Recognition
Yanghao Li, Naiyan Wang, Jiaying Liu +1
Although Deep Convolutional Neural Networks (CNNs) have liberated their power in various computer vision tasks, the most important components of CNN, convolutional layers and fully…
Revisiting Batch Normalization For Practical Domain Adaptation
Yanghao Li, Naiyan Wang, Jianping Shi +2
Deep neural networks (DNN) have shown unprecedented success in various computer vision applications such as image classification and object detection. However, it is still a common…
The Secrets of Salient Object Segmentation
Yin Li, Xiaodi Hou, Christof Koch +2
In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies…
A Meta-Theory of Boundary Detection Benchmarks
Xiaodi Hou, Alan Yuille, Christof Koch
Human labeled datasets, along with their corresponding evaluation algorithms, play an important role in boundary detection. We here present a psychophysical experiment that address…