%0 Generic %1 citeulike:14575637 %A xxx, %D 2018 %K attention detection pooling rcnn %T Learning Region Features for Object Detection %U http://arxiv.org/abs/1803.07066 %X While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work proposes a general viewpoint that unifies existing region feature extraction methods and a novel method that is end-to-end learnable. The proposed method removes most heuristic choices and outperforms its RoI pooling counterparts. It moves further towards fully learnable object detection.

@misc{citeulike:14575637, abstract = {{While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work proposes a general viewpoint that unifies existing region feature extraction methods and a novel method that is end-to-end learnable. The proposed method removes most heuristic choices and outperforms its RoI pooling counterparts. It moves further towards fully learnable object detection.}}, added-at = {2019-02-27T22:23:29.000+0100}, archiveprefix = {arXiv}, author = {xxx}, biburl = {https://www.bibsonomy.org/bibtex/2cc06bdc980280fa731b9cfa9d806fb11/nmatsuk}, citeulike-article-id = {14575637}, citeulike-linkout-0 = {http://arxiv.org/abs/1803.07066}, citeulike-linkout-1 = {http://arxiv.org/pdf/1803.07066}, day = 19, eprint = {1803.07066}, interhash = {59f9cc022600464472ad2fdb0933bc36}, intrahash = {cc06bdc980280fa731b9cfa9d806fb11}, keywords = {attention detection pooling rcnn}, month = mar, posted-at = {2018-04-26 08:45:04}, priority = {0}, timestamp = {2019-02-27T22:23:29.000+0100}, title = {{Learning Region Features for Object Detection}}, url = {http://arxiv.org/abs/1803.07066}, year = 2018 }