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Computer Vision – ECCV 2020 Workshops

Glasgow, UK, August 23–28, 2020, Proceedings, Part VI

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Adrien Bartoli

    1. University of Clermont Auvergne, Clermont Ferrand, France

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    You can also search for this editor in PubMed   Google Scholar

  2. Andrea Fusiello

    1. Università degli Studi di Udine, Udine, Italy

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12540)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: ECCV 2020.

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About this book

The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic.

The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part VI focusses on reassessing the evaluation of object detection; computer vision problems in plant phenotyping; fair face recognition and analysis; and perception through structured generative models.

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Table of contents (39 papers)

  1. Front Matter

    Pages i-xxvi
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  2. W36 - Beyond mAP: Reassessing the Evaluation of Object Detection

    1. Front Matter

      Pages 1-2
      Download chapter PDF

    2. Assessing Box Merging Strategies and Uncertainty Estimation Methods in Multimodel Object Detection

      • Felippe Schmoeller Roza, Maximilian Henne, Karsten Roscher, Stephan Günnemann
      Pages 3-10

    3. Implementing Planning KL-Divergence

      • Jonah Philion, Amlan Kar, Sanja Fidler
      Pages 11-18

    4. ODIN: An Object Detection and Instance Segmentation Diagnosis Framework

      • Rocio Nahime Torres, Piero Fraternali, Jesus Romero
      Pages 19-31

    5. Shift Equivariance in Object Detection

      • Marco Manfredi, Yu Wang
      Pages 32-45

    6. Probabilistic Object Detection with an Ensemble of Experts

      • Dimity Miller
      Pages 46-55

    7. EPrOD: Evolved Probabilistic Object Detector with Diverse Samples

      • Jaewoong Choi, Sungwook Lee, Seunghyun Lee, Byung Cheol Song
      Pages 56-66

    8. Probabilistic Object Detection via Deep Ensembles

      • Zongyao Lyu, Nolan Gutierrez, Aditya Rajguru, William J. Beksi
      Pages 67-75

  3. W37 - Imbalance Problems in Computer Vision

    1. Front Matter

      Pages 77-78
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    2. A Machine Learning Approach to Assess Student Group Collaboration Using Individual Level Behavioral Cues

      • Anirudh Som, Sujeong Kim, Bladimir Lopez-Prado, Svati Dhamija, Nonye Alozie, Amir Tamrakar
      Pages 79-94

    3. Remix: Rebalanced Mixup

      • Hsin-Ping Chou, Shih-Chieh Chang, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
      Pages 95-110

    4. Generalized Many-Way Few-Shot Video Classification

      • Yongqin Xian, Bruno Korbar, Matthijs Douze, Bernt Schiele, Zeynep Akata, Lorenzo Torresani
      Pages 111-127

    5. GAN-Based Anomaly Detection In Imbalance Problems

      • Junbong Kim, Kwanghee Jeong, Hyomin Choi, Kisung Seo
      Pages 128-145

    6. Active Class Incremental Learning for Imbalanced Datasets

      • Eden Belouadah, Adrian Popescu, Umang Aggarwal, Léo Saci
      Pages 146-162

    7. Knowledge Distillation for Multi-task Learning

      • Wei-Hong Li, Hakan Bilen
      Pages 163-176

    8. Mitigating Dataset Imbalance via Joint Generation and Classification

      • Aadarsh Sahoo, Ankit Singh, Rameswar Panda, Rogerio Feris, Abir Das
      Pages 177-193

  4. W40 - Computer Vision Problems in Plant Phenotyping

    1. Front Matter

      Pages 195-196
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    2. Patch-Based CNN Evaluation for Bark Classification

      • Debaleena Misra, Carlos Crispim-Junior, Laure Tougne
      Pages 197-212

    3. Improving Pixel Embedding Learning Through Intermediate Distance Regression Supervision for Instance Segmentation

      • Yuli Wu, Long Chen, Dorit Merhof
      Pages 213-227
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  34. Computer Vision – ECCV 2020 Workshops

  35. Computer Vision – ECCV 2020 Workshops

  36. Computer Vision – ECCV 2020 Workshops

Editors and Affiliations

  • University of Clermont Auvergne, Clermont Ferrand, France

    Adrien Bartoli

  • Università degli Studi di Udine, Udine, Italy

    Andrea Fusiello

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