9 citations · 9 across the 2 of their papers we have counts for
5 papers
Superpixel Segmentation via Convolutional Neural Networks with Regularized Information Maximization
Teppei Suzuki
We propose an unsupervised superpixel segmentation method by optimizing a randomly-initialized convolutional neural network (CNN) in inference time. Our method generates superpixel…
Tabulated MLP for Fast Point Feature Embedding
Yusuke Sekikawa, Teppei Suzuki
Aiming at a drastic speedup for point-data embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptron (MLP) and look-up table (LUT) to transform…
Adversarial Transformations for Semi-Supervised Learning
Teppei Suzuki, Ikuro Sato
We propose a Regularization framework based on Adversarial Transformations (RAT) for semi-supervised learning. RAT is designed to enhance robustness of the output distribution of c…
cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey
Hirokatsu Kataoka, Soma Shirakabe, Yun He +14
The paper gives futuristic challenges disscussed in the cvpaper.challenge. In 2015 and 2016, we thoroughly study 1,600+ papers in several conferences/journals such as CVPR/ICCV/ECC…
Changing Fashion Cultures
Kaori Abe, Teppei Suzuki, Shunya Ueta +3
The paper presents a novel concept that analyzes and visualizes worldwide fashion trends. Our goal is to reveal cutting-edge fashion trends without displaying an ordinary fashion s…