Real-Time Seamless Single Shot 6D Object Pose Prediction

We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or having to examine multiple hypotheses. Unlike a recently proposed single-shot technique for this task (Kehl et al., ICCV'17) that only predicts an approximate 6D pose that must then be refined, ours is accurate enough not to require additional post-processing... (read more)

PDF Abstract CVPR 2018 PDF CVPR 2018 Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
6D Pose Estimation using RGB LineMOD Single-shot Deep CNN Accuracy 90.37% # 7
Mean ADD 55.95 # 12
Mean IoU 99.92 # 1
6D Pose Estimation using RGB OCCLUSION Single-shot deep CNN MAP 0.48 # 1
Drone Pose Estimation UAVA SingleShotPose Normalized Position Error 0.025 # 2
Orientation Error 0.07 # 2
Combined Pose Error 0.095 # 2

Methods used in the Paper


METHOD TYPE
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