Learning rich features from RGB-D images for object detection and segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8695 LNCS, Issue PART 7, 2014, Pages 345-360

  Gupta, Saurabh ^a   Girshick, Ross ^a   Arbeláez, Pablo ^a,b   Malik, Jitendra ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSIDAD DE LOS ANDES   (Colombia)

Author keywords

object detection; object segmentation; RGB D perception

Indexed keywords

IMAGE SEGMENTATION; NEURAL NETWORKS; PIXELS; SEMANTICS;

CLASSIFICATION FRAMEWORK; CONVOLUTIONAL NEURAL NETWORK; FEATURE REPRESENTATION; HEIGHT ABOVE GROUND; HORIZONTAL DISPARITY; OBJECT DETECTION; OBJECT DETECTION SYSTEMS; OBJECT SEGMENTATION;

OBJECT RECOGNITION;

EID: 84906344142     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10584-0_23     Document Type: Conference Paper

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