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Labels Are Not Perfect: Improving Probabilistic Object Detection via
  Label Uncertainty

Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty

10 August 2020
Di Feng
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty"

4 / 4 papers shown
Few-shot Object Counting and Detection
Few-shot Object Counting and DetectionEuropean Conference on Computer Vision (ECCV), 2022
Trung Quoc Nguyen
Chau Pham
Khoi Duc Minh Nguyen
Minh Hoai
265
80
0
22 Jul 2022
Probabilistic Approach for Road-Users Detection
Probabilistic Approach for Road-Users Detection
Gledson Melotti
Weihao Lu
Pedro Conde
Dezong Zhao
A. Asvadi
Nuno Gonçalves
C. Premebida
411
5
0
02 Dec 2021
Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across
  Objects and Views
Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across Objects and Views
Robert McCraith
Eldar Insafutdinov
Lukás Neumann
Andrea Vedaldi
3DPC
309
10
0
16 Sep 2021
A Review and Comparative Study on Probabilistic Object Detection in
  Autonomous Driving
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
Di Feng
Ali Harakeh
Steven Waslander
Klaus C. J. Dietmayer
AAMLUQCVEDL
400
299
0
20 Nov 2020
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