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IVIU-DET Object Detection and Tracking::Detection and tracking of objects

Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications


Performance of 6DoF pose estimation techniques from RGB/RGB-D images has improved significantly with sophisticated deep learning frameworks. These frameworks require large-scale training data based on real/synthetic RGB/RGB-D information. Difficulty of obtaining adequate training data has limited the scope of these frameworks for ubiquitous application areas. Also, fast pose estimation at inference time often requires high-end GPU(s) that restricts the scope for its application in mobile hardware.

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Authors:
Bowen Chen, Juhan Bae, Dibyendu Mukherjee
Submitted On:
18 September 2019 - 1:28pm
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FAST 6DOF POSE ESTIMATION WITH SYNTHETIC TEXTURELESS CAD MODEL FOR MOBILE APPLICATIONS - Poster ICIP_Static.pdf

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[1] Bowen Chen, Juhan Bae, Dibyendu Mukherjee, "Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4690. Accessed: Aug. 09, 2020.
@article{4690-19,
url = {http://sigport.org/4690},
author = {Bowen Chen; Juhan Bae; Dibyendu Mukherjee },
publisher = {IEEE SigPort},
title = {Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications},
year = {2019} }
TY - EJOUR
T1 - Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications
AU - Bowen Chen; Juhan Bae; Dibyendu Mukherjee
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4690
ER -
Bowen Chen, Juhan Bae, Dibyendu Mukherjee. (2019). Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications. IEEE SigPort. http://sigport.org/4690
Bowen Chen, Juhan Bae, Dibyendu Mukherjee, 2019. Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications. Available at: http://sigport.org/4690.
Bowen Chen, Juhan Bae, Dibyendu Mukherjee. (2019). "Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications." Web.
1. Bowen Chen, Juhan Bae, Dibyendu Mukherjee. Fast 6dof Pose Estimation with Synthetic Textureless Cad Model for Mobile Applications [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4690

VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY


Visual tracking is a very important and challenging problem in the field of computer vision. In recent years, Siamese networks have been widely used for visual tracking due to their fast tracking speed, but many trackers based on Siamese network train their networks by utilizing either pairwise loss or triplet loss, which easily leads to over-fitting. In addition, it is difficult to distinguish some hard samples in the training samples. In this paper, we propose a novel global similarity loss to train the network.

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Authors:
Chao Fan,Yulong Wang,Chenglong Li,Jin Tang
Submitted On:
16 September 2019 - 5:20am
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VISUAL TRACKING

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[1] Chao Fan,Yulong Wang,Chenglong Li,Jin Tang, "VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4638. Accessed: Aug. 09, 2020.
@article{4638-19,
url = {http://sigport.org/4638},
author = {Chao Fan;Yulong Wang;Chenglong Li;Jin Tang },
publisher = {IEEE SigPort},
title = {VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY},
year = {2019} }
TY - EJOUR
T1 - VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY
AU - Chao Fan;Yulong Wang;Chenglong Li;Jin Tang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4638
ER -
Chao Fan,Yulong Wang,Chenglong Li,Jin Tang. (2019). VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY. IEEE SigPort. http://sigport.org/4638
Chao Fan,Yulong Wang,Chenglong Li,Jin Tang, 2019. VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY. Available at: http://sigport.org/4638.
Chao Fan,Yulong Wang,Chenglong Li,Jin Tang. (2019). "VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY." Web.
1. Chao Fan,Yulong Wang,Chenglong Li,Jin Tang. VISUAL TRACKING VIA SIAMESE NETWORK WITH GLOBAL SIMILARITY [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4638