5 citations · 19 across the 8 of their papers we have counts for
6 papers · 1 filter
Object Memory Transformer for Object Goal Navigation
Rui Fukushima, Kei Ota, Asako Kanezaki +2
This paper presents a reinforcement learning method for object goal navigation (ObjNav) where an agent navigates in 3D indoor environments to reach a target object based on long-te…
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…
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds
Xuanyu Yin, Yoko Sasaki, Weimin Wang +1
Lidar based 3D object detection and classification tasks are essential for autonomous driving(AD). A lidar sensor can provide the 3D point cloud data reconstruction of the surround…
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud
Xuanyu YIN, Yoko SASAKI, Weimin WANG +1
Lidar based 3D object detection and classification tasks are essential for automated driving(AD). A Lidar sensor can provide the 3D point coud data reconstruction of the surroundin…
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…
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…