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Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place
  Recognition

Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition

10 January 2022
M. Usman Maqbool Bhutta
Yuxiang Sun
Darwin Lau
Meilin Liu
ArXivPDFHTML

Papers citing "Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition"

2 / 2 papers shown
Title
Multiple Hypothesis Semantic Mapping for Robust Data Association
Multiple Hypothesis Semantic Mapping for Robust Data Association
Lukas Bernreiter
Abel Gawel
H. Sommer
Juan I. Nieto
Roland Siegwart
C. C. Lerma
36
21
0
08 Dec 2020
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State
  Estimator
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Tong Qin
Peiliang Li
Shaojie Shen
51
3,308
0
13 Aug 2017
1