Presentation 2020-12-18
Estimating 3D regions for grasping an object
Atsuki Tsukamoto, Kiyoshi Kogure,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper proposes a method for estimating 3D regions for object grasping. The method takes as its inputs two RGB images, each from one of two stereo cameras, and translates them into object grasping region images, from which it estimates 3D object grasping regions based on stereo matching. The translation is conducted using fully convolutional networks. The method has been evaluated experimentally with four kinds of fully convolutional network models, that is, two kinds of single task models and two kinds of multi-task models, each with object region estimation task as its auxiliary task. The experimental results show that the proposed method can estimate 3D regions for object grasping for all of these four kinds of models.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) object grasping / fully convolutional network / multi-task learning
Paper # PRMU2020-65
Date of Issue 2020-12-10 (PRMU)

Conference Information
Committee PRMU
Conference Date 2020/12/17(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Transfer learning and few shot learning
Chair Yoichi Sato(Univ. of Tokyo)
Vice Chair Akisato Kimura(NTT) / Masakazu Iwamura(Osaka Pref. Univ.)
Secretary Akisato Kimura(Mobility Technologies) / Masakazu Iwamura(Chubu Univ.)
Assistant Takashi Shibata(NTT) / Masashi Nishiyama(Tottori Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Estimating 3D regions for grasping an object
Sub Title (in English)
Keyword(1) object grasping
Keyword(2) fully convolutional network
Keyword(3) multi-task learning
1st Author's Name Atsuki Tsukamoto
1st Author's Affiliation Kanazawa Institute of Technology(KIT)
2nd Author's Name Kiyoshi Kogure
2nd Author's Affiliation Kanazawa Institute of Technology(KIT)
Date 2020-12-18
Paper # PRMU2020-65
Volume (vol) vol.120
Number (no) PRMU-300
Page pp.pp.156-160(PRMU),
#Pages 5
Date of Issue 2020-12-10 (PRMU)