Learning Rich Features from RGB-D Images for Object Detection and Segmentation

22 July 2014

Papers citing "Learning Rich Features from RGB-D Images for Object Detection and Segmentation"

7 / 57 papers shown

Title
SceneNet: Understanding Real World Indoor Scenes With Synthetic Data Ankur Handa Viorica Patraucean Vijay Badrinarayanan Simon Stent R. Cipolla 3DPC 3DV 21 230 0 22 Nov 2015
Vision System and Depth Processing for DRC-HUBO+ Inwook Shim Seunghak Shin Yunsu Bok Kyungdon Joo Dong-Geol Choi Joon-Young Lee Jaesik Park Jun-Ho Oh In So Kweon MDE 31 13 0 21 Sep 2015
Depth-based hand pose estimation: methods, data, and challenges J. Supančič Grégory Rogez Yi Yang Jamie Shotton Deva Ramanan 3DH 13 116 0 24 Apr 2015
Holistically-Nested Edge Detection Saining Xie Z. Tu 18 3,456 0 24 Apr 2015
Predicting Complete 3D Models of Indoor Scenes Ruiqi Guo Chuhang Zou Derek Hoiem 3DV 9 57 0 09 Apr 2015
Do More Dropouts in Pool5 Feature Maps for Better Object Detection Zhiqiang Shen Xiangyang Xue 22 5 0 24 Sep 2014
Indoor Semantic Segmentation using depth information Camille Couprie C. Farabet Laurent Najman Yann LeCun SSeg MDE 68 473 0 16 Jan 2013