Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses Seungwoo Y oo Juil Koo Kyeongmin Y eo Minhyuk Sung KAIST {dreamy1534,63days,aaaaa,mhsung }@kaist.ac.kr

To better distill pose information from the object's geometry, we propose the implicit pose applier to output an intrinsic mesh property, the face Jacobian. Once the extracted pose information is transferred to the target object, the pose applier is fine-tuned in a self-supervised manner to better describe the target object's shapes with pose