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

Keyphrases

• Depth Image 100%
• Object Detection 100%
• RGB-D 100%
• Object Segmentation 100%
• Relative Improvement 100%
• Learned Features 50%
• Image Features 50%
• Classification Framework 50%
• Robotics 50%
• Unary 50%
• Detection Window 50%
• Object Categories 50%
• Binary Hypothesis Testing 50%
• Feature Representation 50%
• Object Instance 50%
• Object Detector 50%
• Convolutional Neural Network 50%
• Object Detection System 50%
• Depth Feature 50%
• Instance Segmentation 50%
• Pose Feature 50%
• Horizontal Disparity 50%
• Sub-pixel Classification 50%
• Semantic Scene Segmentation 50%
• Geocentric Pose 50%
• Decision Forest 50%

Computer Science

• Object Detection 100%
• RGB-D Image 100%
• Representation Learning 33%
• Object Category 33%
• Object Instance 33%
• Object Detector 33%
• Classification Framework 33%
• Superpixel 33%
• Convolutional Neural Network 33%
• Instance Segmentation 33%