Sim2Real Instance-Level Style Transfer for 6D Pose Estimation
Takuya Ikeda,Suomi Tanishige,Ayako Amma,Michael Sudano,Hervé Audren,Koichi Nishiwaki,Takuya Ikeda,Suomi Tanishige,Ayako Amma,Michael Sudano,Hervé Audren,Koichi Nishiwaki
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. However, there are still non-trivial domain gaps, such as differences in textures/materials, between synthetic and real data. These gaps have a measurable impact on performance. To solve this problem, we introduce a simulatio...
