Search Results for author: Anil Armagan

Found 7 papers, 1 papers with code

Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images

no code implementations27 Mar 2020 Juil Sock, Guillermo Garcia-Hernando, Anil Armagan, Tae-Kyun Kim

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.

6D Pose Estimation using RGB Domain Adaptation +2

Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction

no code implementations23 Oct 2019 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.

6D Pose Estimation using RGB Object

Learning to Align Semantic Segmentation and 2.5D Maps for Geolocalization

no code implementations CVPR 2017 Anil Armagan, Martin Hirzer, Peter M. Roth, Vincent Lepetit

We present an efficient method for geolocalization in urban environments starting from a coarse estimate of the location provided by a GPS and using a simple untextured 2. 5D model of the surrounding buildings.

Semantic Segmentation

What is usual in unusual videos? Trajectory snippet histograms for discovering unusualness

no code implementations3 Jan 2014 Ahmet Iscen, Anil Armagan, Pinar Duygulu

Unusual events are important as being possible indicators of undesired consequences.

Cannot find the paper you are looking for? You can Submit a new open access paper.