DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

CVPR 2019 Chen WangDanfei XuYuke ZhuRoberto Martín-MartínCewu LuLi Fei-FeiSilvio Savarese

A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources. Prior works either extract information from the RGB image and depth separately or use costly post-processing steps, limiting their performances in highly cluttered scenes and real-time applications... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
6D Pose Estimation using RGBD LineMOD DeepFusion Mean ADD 94.3 # 3
6D Pose Estimation LineMOD DenseFusion Accuracy (ADD) 94.3 # 2
6D Pose Estimation using RGB YCB-Video DenseFusion Mean AUC 93.1% # 2
6D Pose Estimation YCB-Video DenseFusion ADDS AUC 93.1 # 2

Methods used in the Paper


METHOD TYPE
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