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cs.CV2022
Probabilistic Rotation Representation With an Efficiently Computable Bingham Loss Function and Its Application to Pose Estimation
Hiroya Sato, Takuya Ikeda, Koichi Nishiwaki
In recent years, a deep learning framework has been widely used for object pose estimation. While quaternion is a common choice for rotation representation of 6D pose, it cannot re…
cs.CV2022
Sim2Real Instance-Level Style Transfer for 6D Pose Estimation
Takuya Ikeda, Suomi Tanishige, Ayako Amma +3
In recent years, synthetic data has been widely used in the training of 6D pose estimation networks, in part because it automatically provides perfect annotation at low cost. Howev…