Tanner Schmidt
Tanner Schmidt
Facebook Reality Labs
Verifierad e-postadress på oculus.com - Startsida
Citeras av
Citeras av
Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Y Xiang, T Schmidt, V Narayanan, D Fox
arXiv preprint arXiv:1711.00199, 2017
DART: Dense Articulated Real-Time Tracking.
T Schmidt, RA Newcombe, D Fox
Robotics: Science and Systems 2 (1), 2014
Self-supervised visual descriptor learning for dense correspondence
T Schmidt, R Newcombe, D Fox
IEEE Robotics and Automation Letters 2 (2), 420-427, 2016
Depth-based tracking with physical constraints for robot manipulation
T Schmidt, K Hertkorn, R Newcombe, Z Marton, M Suppa, D Fox
2015 IEEE International Conference on Robotics and Automation (ICRA), 119-126, 2015
DART: dense articulated real-time tracking with consumer depth cameras
T Schmidt, R Newcombe, D Fox
Autonomous Robots 39 (3), 239-258, 2015
Dynamic high resolution deformable articulated tracking
A Walsman, W Wan, T Schmidt, D Fox
2017 International Conference on 3D Vision (3DV), 38-47, 2017
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction
R Chabra, JE Lenssen, E Ilg, T Schmidt, J Straub, S Lovegrove, ...
arXiv preprint arXiv:2003.10983, 2020
FroDO: From Detections to 3D Objects
K Li, M Rünz, M Tang, L Ma, C Kong, T Schmidt, I Reid, L Agapito, ...
arXiv preprint arXiv:2005.05125, 2020
Self-directed Lifelong Learning for Robot Vision
T Schmidt, D Fox
Robotics Research, 109-114, 2020
FroDO: From Detections to 3D Objects
M Runz, K Li, M Tang, L Ma, C Kong, T Schmidt, I Reid, L Agapito, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Model-Based Self-Supervision for Fine-Grained Image Understanding
T Schmidt
Four Dimensional Mapping with RGB-D Sensors and Mobile Robots
T Schmidt
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–12