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16th ECCV Workshops 2020: Glasgow, UK - Part VI
- Adrien Bartoli, Andrea Fusiello:

Computer Vision - ECCV 2020 Workshops - Glasgow, UK, August 23-28, 2020, Proceedings, Part VI. Lecture Notes in Computer Science 12540, Springer 2020, ISBN 978-3-030-65413-9
W36 - Beyond mAP: Reassessing the Evaluation of Object Detection
- Felippe Schmoeller Roza

, Maximilian Henne, Karsten Roscher, Stephan Günnemann:
Assessing Box Merging Strategies and Uncertainty Estimation Methods in Multimodel Object Detection. 3-10 - Jonah Philion, Amlan Kar, Sanja Fidler:

Implementing Planning KL-Divergence. 11-18 - Rocio Nahime Torres, Piero Fraternali, Jesus Romero:

ODIN: An Object Detection and Instance Segmentation Diagnosis Framework. 19-31 - Marco Manfredi

, Yu Wang
:
Shift Equivariance in Object Detection. 32-45 - Dimity Miller

:
Probabilistic Object Detection with an Ensemble of Experts. 46-55 - Jaewoong Choi, Sungwook Lee, Seunghyun Lee, Byung Cheol Song:

EPrOD: Evolved Probabilistic Object Detector with Diverse Samples. 56-66 - Zongyao Lyu

, Nolan Gutierrez
, Aditya Rajguru
, William J. Beksi
:
Probabilistic Object Detection via Deep Ensembles. 67-75
W37 - Imbalance Problems in Computer Vision
- Anirudh Som, Sujeong Kim, Bladimir Lopez-Prado, Svati Dhamija, Nonye Alozie, Amir Tamrakar:

A Machine Learning Approach to Assess Student Group Collaboration Using Individual Level Behavioral Cues. 79-94 - Hsin-Ping Chou, Shih-Chieh Chang

, Jia-Yu Pan, Wei Wei, Da-Cheng Juan:
Remix: Rebalanced Mixup. 95-110 - Yongqin Xian, Bruno Korbar, Matthijs Douze, Bernt Schiele, Zeynep Akata, Lorenzo Torresani:

Generalized Many-Way Few-Shot Video Classification. 111-127 - Junbong Kim, Kwanghee Jeong, Hyomin Choi, Kisung Seo:

GAN-Based Anomaly Detection In Imbalance Problems. 128-145 - Eden Belouadah

, Adrian Popescu
, Umang Aggarwal
, Léo Saci
:
Active Class Incremental Learning for Imbalanced Datasets. 146-162 - Wei-Hong Li, Hakan Bilen:

Knowledge Distillation for Multi-task Learning. 163-176 - Aadarsh Sahoo, Ankit Singh, Rameswar Panda, Rogério Schmidt Feris, Abir Das

:
Mitigating Dataset Imbalance via Joint Generation and Classification. 177-193
W40 - Computer Vision Problems in Plant Phenotyping
- Debaleena Misra, Carlos Fernando Crispim Junior, Laure Tougne

:
Patch-Based CNN Evaluation for Bark Classification. 197-212 - Yuli Wu

, Long Chen
, Dorit Merhof
:
Improving Pixel Embedding Learning Through Intermediate Distance Regression Supervision for Instance Segmentation. 213-227 - Sruti Das Choudhury

:
Time Series Modeling for Phenotypic Prediction and Phenotype-Genotype Mapping Using Neural Networks. 228-243 - Ayan Chaudhury

, Frédéric Boudon
, Christophe Godin
:
3D Plant Phenotyping: All You Need is Labelled Point Cloud Data. 244-260 - Faina Khoroshevsky

, Stanislav Khoroshevsky, Oshry Markovich, Orit Granitz, Aharon Bar-Hillel:
Phenotyping Problems of Parts-per-Object Count. 261-278 - Sagi Levanon, Oshry Markovich, Itamar Gozlan, Ortal Bakhshian, Alon Zvirin, Yaron Honen, Ron Kimmel:

Abiotic Stress Prediction from RGB-T Images of Banana Plantlets. 279-295 - Mathieu Gaillard

, Chenyong Miao
, James C. Schnable
, Bedrich Benes
:
Sorghum Segmentation by Skeleton Extraction. 296-311 - Matthias Körschens

, Paul Bodesheim
, Christine Römermann
, Solveig Franziska Bucher
, Josephine Ulrich
, Joachim Denzler
:
Towards Confirmable Automated Plant Cover Determination. 312-329 - Tewodros W. Ayalew, Jordan R. Ubbens

, Ian Stavness:
Unsupervised Domain Adaptation for Plant Organ Counting. 330-346 - Jonas Bömer

, Laura Zabawa, Philipp Sieren, Anna Kicherer, Lasse Klingbeil, Uwe Rascher
, Onno Muller, Heiner Kuhlmann
, Ribana Roscher:
Automatic Differentiation of Damaged and Unharmed Grapes Using RGB Images and Convolutional Neural Networks. 347-359 - Hanno Scharr

, Benjamin Bruns
, Andreas Fischbach
, Johanna Roussel
, Lukas Scholtes
, Jonas vom Stein
:
Germination Detection of Seedlings in Soil: A System, Dataset and Challenge. 360-374 - Omer Wosner, Guy Farjon, Faina Khoroshevsky

, Lena Karol, Oshry Markovich, Daniel A. Koster, Aharon Bar-Hillel:
Detection in Agricultural Contexts: Are We Close to Human Level? 375-390 - Jordan R. Ubbens

, Tewodros W. Ayalew, Steve Shirtliffe
, Anique Josuttes, Curtis Pozniak, Ian Stavness:
AutoCount: Unsupervised Segmentation and Counting of Organs in Field Images. 391-399 - Dewi Endah Kharismawati

, Hadi Ali Akbarpour
, Rumana Aktar
, Filiz Bunyak
, Kannappan Palaniappan
, Toni Kazic
:
CorNet: Unsupervised Deep Homography Estimation for Agricultural Aerial Imagery. 400-417 - Jonas Krause

, Kyungim Baek, Lipyeow Lim:
Expanding CNN-Based Plant Phenotyping Systems to Larger Environments. 418-432 - Guohao Yu

, Alina Zare
, Weihuang Xu
, Roser Matamala
, Joel Reyes-Cabrera
, Felix B. Fritschi
, Thomas E. Juenger
:
Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM. 433-449 - Yifan Wu, Ya-Han Hu, Lei Li:

BTWD: Bag of Tricks for Wheat Detection. 450-460
W41 - Fair Face Recognition and Analysis
- Tomás Sixta, Júlio C. S. Jacques Júnior

, Pau Buch-Cardona, Eduard Vazquez, Sergio Escalera
:
FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition. 463-481 - Shengyao Zhou, Junfan Luo, Junkun Zhou, Xiang Ji:

AsArcFace: Asymmetric Additive Angular Margin Loss for Fairface Recognition. 482-491 - Jun Yu, Xinlong Hao, Haonian Xie, Ye Yu:

Fair Face Recognition Using Data Balancing, Enhancement and Fusion. 492-505 - Tian Xu, Jennifer White, Sinan Kalkan, Hatice Gunes:

Investigating Bias and Fairness in Facial Expression Recognition. 506-523 - Amlaan Kar, Maneet Singh, Mayank Vatsa, Richa Singh:

Disguised Face Verification Using Inverse Disguise Quality. 524-540
W44 - Perception Through Structured Generative Models
- Weiyu Du, Oleh Rybkin, Lingzhi Zhang, Jianbo Shi:

Toward Continuous-Time Representations of Human Motion. 543-548 - Sarthak Bhagat, Vishaal Udandarao, Shagun Uppal, Saket Anand:

DisCont: Self-Supervised Visual Attribute Disentanglement Using Context Vectors. 549-553 - Vadim Sushko, Edgar Schönfeld, Dan Zhang, Jürgen Gall, Bernt Schiele, Anna Khoreva:

3D Noise and Adversarial Supervision Is All You Need for Multi-modal Semantic Image Synthesis. 554-558

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