Helpful Brief: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023. In this work, we introduce a new technique that combines two popular methods to estimate uncertainty in

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In this work, we introduce a new technique that combines two popular methods to estimate uncertainty in Authors: Shi, Xuepeng*; Chen, Zhixiang; Kim, Tae-Kyun Description: In autonomous driving, monocular 3D

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Jiwoong Choi, Ismail Elezi, Hyuk-Jae Lee, Clement Farabet, Jose M Alvarez; Active Learning for Deep IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023.

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  • Jiwoong Choi, Ismail Elezi, Hyuk-Jae Lee, Clement Farabet, Jose M Alvarez; Active Learning for Deep
  • Authors: Shi, Xuepeng*; Chen, Zhixiang; Kim, Tae-Kyun Description: In autonomous driving, monocular 3D
  • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023.
  • In this work, we introduce a new technique that combines two popular methods to estimate uncertainty in

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Object Detection as Probabilistic Set Prediction [ECCV2022]
Sungwook Lee | EPrOD: Evolved Probabilistic Object Detector with Diverse Samples | ECCV 2020 BMREOD
Dimity Miller | Probabilistic Object Detection with an Ensemble of Experts | ECCV 2020 - BMREOD
An Uncertainty Estimation Framework for Probabilistic Object Detection
Zongyao Lyu | Probabilistic Object Detection via Deep Ensembles | ECCV 2020 - BMREOD
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty
[CVPR 2023] PROB: Probabilistic Objectness for Open World Object Detection
Multivariate Probabilistic Monocular 3D Object Detection
Active Learning for Deep Object Detection via Probabilistic Modeling (ICCV 2021)
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Read Practical Notes
Object Detection as Probabilistic Set Prediction [ECCV2022]

Object Detection as Probabilistic Set Prediction [ECCV2022]

Read more details and related context about Object Detection as Probabilistic Set Prediction [ECCV2022].

Sungwook Lee | EPrOD: Evolved Probabilistic Object Detector with Diverse Samples | ECCV 2020 BMREOD

Sungwook Lee | EPrOD: Evolved Probabilistic Object Detector with Diverse Samples | ECCV 2020 BMREOD

Read more details and related context about Sungwook Lee | EPrOD: Evolved Probabilistic Object Detector with Diverse Samples | ECCV 2020 BMREOD.

Dimity Miller | Probabilistic Object Detection with an Ensemble of Experts | ECCV 2020 - BMREOD

Dimity Miller | Probabilistic Object Detection with an Ensemble of Experts | ECCV 2020 - BMREOD

Read more details and related context about Dimity Miller | Probabilistic Object Detection with an Ensemble of Experts | ECCV 2020 - BMREOD.

An Uncertainty Estimation Framework for Probabilistic Object Detection

An Uncertainty Estimation Framework for Probabilistic Object Detection

In this work, we introduce a new technique that combines two popular methods to estimate uncertainty in

Zongyao Lyu | Probabilistic Object Detection via Deep Ensembles | ECCV 2020 - BMREOD

Zongyao Lyu | Probabilistic Object Detection via Deep Ensembles | ECCV 2020 - BMREOD

Read more details and related context about Zongyao Lyu | Probabilistic Object Detection via Deep Ensembles | ECCV 2020 - BMREOD.

BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video

BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023. Paper:

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

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

Read more details and related context about Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty.

[CVPR 2023] PROB: Probabilistic Objectness for Open World Object Detection

[CVPR 2023] PROB: Probabilistic Objectness for Open World Object Detection

Read more details and related context about [CVPR 2023] PROB: Probabilistic Objectness for Open World Object Detection.

Multivariate Probabilistic Monocular 3D Object Detection

Multivariate Probabilistic Monocular 3D Object Detection

Authors: Shi, Xuepeng*; Chen, Zhixiang; Kim, Tae-Kyun Description: In autonomous driving, monocular 3D

Active Learning for Deep Object Detection via Probabilistic Modeling (ICCV 2021)

Active Learning for Deep Object Detection via Probabilistic Modeling (ICCV 2021)

Jiwoong Choi, Ismail Elezi, Hyuk-Jae Lee, Clement Farabet, Jose M Alvarez; Active Learning for Deep