Multimodal Convolutional Neural Network for Object Detection Using RGB-D Images

被引:0
|
作者
Mocanu, Irina [1 ]
Clapon, Cosmin [1 ]
机构
[1] Univ Politehn Bucuresti, Comp Sci Dept, Bucharest, Romania
基金
欧盟地平线“2020”;
关键词
object detection; convolutional neural network; RGB-D images;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a new convolutional neural network architecture for performing object detection based on RGB-D images. The network is an extension of the Faster-RCNN network where we add an additional input network branch for processing the depth image. The network was evaluated on the SUN RGB-D dataset for object detection and we obtained a positive difference in mAP score of about 4%, compared to the original one.
引用
收藏
页码:307 / 310
页数:4
相关论文
共 50 条
  • [1] Fast 3D Object Detection with RGB-D Images Using Graph Convolutional Network
    Takahashi, Masahiro
    Kitsukawa, Takumi
    Moro, Alessandro
    Umeda, Kazunori
    2022 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII 2022), 2022, : 395 - 400
  • [2] RGB-D OBJECT RECOGNITION WITH MULTIMODAL DEEP CONVOLUTIONAL NEURAL NETWORKS
    Rahman, Mohammad Muntasir
    Tan, Yanhao
    Xue, Jian
    Lu, Ke
    2017 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2017, : 991 - 996
  • [3] Vehicle Detection Algorithm Based on Convolutional Neural Network and RGB-D Images
    Wang Decheng
    Chen Xiangning
    Feng, Zhao
    Sun Haoran
    LASER & OPTOELECTRONICS PROGRESS, 2019, 56 (18)
  • [4] Grading Fruits and Vegetables Using RGB-D Images and Convolutional Neural Network
    Nishi, Toshiki
    Kurogi, Shuichi
    Matsuo, Kazuya
    2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 3222 - 3227
  • [5] Joint Detection of RGB-D Images Based on Double Flow Convolutional Neural Network
    Liu fan
    Liu Pengyuan
    Zhang Junning
    Xu Binbin
    LASER & OPTOELECTRONICS PROGRESS, 2018, 55 (02)
  • [6] Multimodal Neural Networks: RGB-D for Semantic Segmentation and Object Detection
    Schneider, Lukas
    Jasch, Manuel
    Froehlich, Bjoern
    Weber, Thomas
    Franke, Uwe
    Pollefeys, Marc
    Raetsch, Matthias
    IMAGE ANALYSIS, SCIA 2017, PT I, 2017, 10269 : 98 - 109
  • [7] Hybrid RGB-D Object Recognition using Convolutional Neural Network and Fisher Vector
    Li, Wei
    Cao, Zhiguo
    Xiao, Yang
    Fang, Zhiwen
    2015 CHINESE AUTOMATION CONGRESS (CAC), 2015, : 506 - 511
  • [8] RGB-D Object Recognition Using Deep Convolutional Neural Networks
    Zia, Saman
    Yuksel, Buket
    Yuret, Deniz
    Yemez, Yucel
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017), 2017, : 887 - 894
  • [9] Salient object detection for RGB-D images by generative adversarial network
    Liu, Zhengyi
    Tang, Jiting
    Xiang, Qian
    Zhao, Peng
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (35-36) : 25403 - 25425
  • [10] Salient object detection for RGB-D images by generative adversarial network
    Zhengyi Liu
    Jiting Tang
    Qian Xiang
    Peng Zhao
    Multimedia Tools and Applications, 2020, 79 : 25403 - 25425