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S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking
  with Adaptive Spatio-Temporal Appearance Representations
v1v2 (latest)

S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations

30 June 2023
Simon Doll
Niklas Hanselmann
Lukas Schneider
Richard Schulz
Markus Enzweiler
Hendrik P. A. Lensch
ArXiv (abs)PDFHTML

Papers citing "S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations"

2 / 2 papers shown
Title
DualAD: Disentangling the Dynamic and Static World for End-to-End
  Driving
DualAD: Disentangling the Dynamic and Static World for End-to-End Driving
Simon Doll
Niklas Hanselmann
Lukas Schneider
Richard Schulz
Marius Cordts
Markus Enzweiler
Hendrik P. A. Lensch
75
8
0
10 Jun 2024
Quasi-Dense Similarity Learning for Multiple Object Tracking
Quasi-Dense Similarity Learning for Multiple Object Tracking
Jiangmiao Pang
Linlu Qiu
Xia Li
Haofeng Chen
Qi Li
Trevor Darrell
Feng Yu
VOT
199
375
0
11 Jun 2020
1