1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2022★ 1 cited
CRT-6D: Fast 6D Object Pose Estimation with Cascaded Refinement Transformers
Pedro Castro, Tae-Kyun Kim
Learning based 6D object pose estimation methods rely on computing large intermediate pose representations and/or iteratively refining an initial estimation with a slow render-comp…
cs.CV2020
Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images
Juil Sock, Guillermo Garcia-Hernando, Anil Armagan +1
Most successful approaches to estimate the 6D pose of an object typically train a neural network by supervising the learning with annotated poses in real world images. These annota…
cs.CV2019
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
Pedro Castro, Anil Armagan, Tae-Kyun Kim
Current 6D object pose methods consist of deep CNN models fully optimized for a single object but with its architecture standardized among objects with different shapes. In contras…