Yi Li, Gu Wang, Xiangyang Ji, Yu Xiang, Dieter Fox . In European Conference on Computer Vision (ECCV), 2018 (oral).In this work, we propose DeepIM, a new refinement technique based on a deep neural network for iterative 6D pose matching. Given an initial 6D pose estimation of an object in a test image, DeepIM predicts a relative SE(3) trans- formation that matches a rendered view of the object against the observed image.