论文信息 - Design of Convolutional Neural Network for Classifying Depth Prediction Images from Overhead

Design of Convolutional Neural Network for Classifying Depth Prediction Images from Overhead

We predict depth of some objects, such a person, chairs and a soccer ball and so on, in overhead images with Fully Convolutional Residual Networks (FCRN) [1]. This networks can predict depth of RGB images taken by monocular cameras. And we classify images predicted depth. Thus we aim at differentiating person or other objects.

Yoshifumi Nishio | Yoko Uwate | Yuichi Miyata | Shu Sumimoto | Ryuta Yoshimura

[1] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[2] Nassir Navab,et al. Deeper Depth Prediction with Fully Convolutional Residual Networks , 2016, 2016 Fourth International Conference on 3D Vision (3DV).

[3] Ali Farhadi,et al. YOLOv3: An Incremental Improvement , 2018, ArXiv.