%0 Generic %1 citeulike:14576961 %A xxx, %D 2018 %K keypoints pooling segmentation %T Pose2Seg: Human Instance Segmentation Without Detection %U http://arxiv.org/abs/1803.10683 %X The general method of image instance segmentation is to perform the object detection first, and then segment the object from the detection bounding-box. More recently, deep learning methods like Mask R-CNN perform them jointly. However, little research takes into account the uniqueness of the "1human" category, which can be well defined by the pose skeleton. In this paper, we present a brand new pose-based instance segmentation framework for humans which separates instances based on human pose, not proposal region detection. We demonstrate that our pose-based framework can achieve similar accuracy to the detection-based approach, and can moreover better handle occlusion, which is the most challenging problem in the detection-based framework.

@misc{citeulike:14576961, abstract = {{The general method of image instance segmentation is to perform the object detection first, and then segment the object from the detection bounding-box. More recently, deep learning methods like Mask R-CNN perform them jointly. However, little research takes into account the uniqueness of the "1human" category, which can be well defined by the pose skeleton. In this paper, we present a brand new pose-based instance segmentation framework for humans which separates instances based on human pose, not proposal region detection. We demonstrate that our pose-based framework can achieve similar accuracy to the detection-based approach, and can moreover better handle occlusion, which is the most challenging problem in the detection-based framework.}}, added-at = {2019-02-27T22:23:29.000+0100}, archiveprefix = {arXiv}, author = {xxx}, biburl = {https://www.bibsonomy.org/bibtex/2a7744d5c2104f5bf7ee30a45dc8601d0/nmatsuk}, citeulike-article-id = {14576961}, citeulike-linkout-0 = {http://arxiv.org/abs/1803.10683}, citeulike-linkout-1 = {http://arxiv.org/pdf/1803.10683}, day = 28, eprint = {1803.10683}, interhash = {ce04dc8fe1870a4ee8b93682a68ca5d1}, intrahash = {a7744d5c2104f5bf7ee30a45dc8601d0}, keywords = {keypoints pooling segmentation}, month = mar, posted-at = {2018-04-28 08:21:19}, priority = {0}, timestamp = {2019-02-27T22:23:29.000+0100}, title = {{Pose2Seg: Human Instance Segmentation Without Detection}}, url = {http://arxiv.org/abs/1803.10683}, year = 2018 }