most citedUnsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering

253 citations · 255 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Adaptive Future Frame Prediction with Ensemble Network

Wonjik Kim, Masayuki Tanaka, Masatoshi Okutomi +1

Future frame prediction in videos is a challenging problem because videos include complicated movements and large appearance changes. Learning-based future frame prediction approac…

cs.CV2020

Human Segmentation with Dynamic LiDAR Data

Tao Zhong, Wonjik Kim, Masayuki Tanaka +1

Consecutive LiDAR scans compose dynamic 3D sequences, which contain more abundant information than a single frame. Similar to the development history of image and video perception,…

cs.CV2020253 cited

Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering

Wonjik Kim, Asako Kanezaki, Masayuki Tanaka

The usage of convolutional neural networks (CNNs) for unsupervised image segmentation was investigated in this study. In the proposed approach, label prediction and network paramet…

cs.CV2020

Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training

Wonjik Kim, Masayuki Tanaka, Masatoshi Okutomi +1

In this paper, we propose an automatic labeled sequential data generation pipeline for human segmentation and velocity estimation with point clouds. Considering the impact of deep…

cs.CV20192 cited

Automatic Labeled LiDAR Data Generation based on Precise Human Model

Wonjik Kim, Masayuki Tanaka, Masatoshi Okutomi +1

Following improvements in deep neural networks, state-of-the-art networks have been proposed for human recognition using point clouds captured by LiDAR. However, the performance of…