1 code implementation • CVPR 2023 • HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai, Nikolas Brasch, Yitong Li, Yannick Verdie, Jifei Song, Yiren Zhou, Anil Armagan, Slobodan Ilic, Ales Leonardis, Nassir Navab, Benjamin Busam
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data.
no code implementations • 9 May 2022 • HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai, Nikolas Brasch, Yitong Li, Yannick Verdie, Jifei Song, Yiren Zhou, Anil Armagan, Slobodan Ilic, Ales Leonardis, Benjamin Busam
Depth estimation is a core task in 3D computer vision.
no code implementations • ECCV 2020 • Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek, Shreyas Hampali, Mahdi Rad, Zhaohui Zhang, Shipeng Xie, Mingxiu Chen, Boshen Zhang, Fu Xiong, Yang Xiao, Zhiguo Cao, Junsong Yuan, Pengfei Ren, Weiting Huang, Haifeng Sun, Marek Hrúz, Jakub Kanis, Zdeněk Krňoul, Qingfu Wan, Shile Li, Linlin Yang, Dongheui Lee, Angela Yao, Weiguo Zhou, Sijia Mei, Yun-hui Liu, Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Philippe Weinzaepfel, Romain Brégier, Grégory Rogez, Vincent Lepetit, Tae-Kyun Kim
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.
no code implementations • 27 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.
no code implementations • 23 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.
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.
no code implementations • 3 Jan 2014 • Ahmet Iscen, Anil Armagan, Pinar Duygulu
Unusual events are important as being possible indicators of undesired consequences.