Buch, Englisch, Band 12540, 560 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 879 g
Glasgow, UK, August 23-28, 2020, Proceedings, Part VI
Buch, Englisch, Band 12540, 560 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 879 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-030-65413-9
Verlag: Springer International Publishing
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
W36 - Beyond mAP: Reassessing the Evaluation of Object Detection.- Assessing Box Merging Strategies and Uncertainty Estimation Methods in Multimodel Object Detection.- Implementing Planning KL-Divergence.- ODIN: an Object Detection and Instance Segmentation Diagnosis Framework.- Shift Equivariance in Object Detection.- Probabilistic Object Detection with an Ensemble of Experts.- EPrOD: Evolved Probabilistic Object Detector with Diverse Samples.- Probabilistic Object Detection via Deep Ensembles.- W37 - Imbalance Problems in Computer Vision.- A Machine Learning Approach to Assess Student Group Collaboration Using Individual Level Behavioral Cues.- Remix: Rebalanced Mixup.- Generalized Many-Way Few-Shot Video Classification.- GAN-Based Anomaly Detection in Imbalance Problems.- Active Class Incremental Learning for Imbalanced Datasets.- Knowledge Distillation for Multi-task Learning.- Mitigating Dataset Imbalance via Joint Generation and Classification.- W40 - Computer Vision Problems inPlant Phenotyping.- Patch-based CNN evaluation for bark classification.- Improving Pixel Embedding Learning through Intermediate Distance Regression Supervision for Instance Segmentation.- Time Series Modeling for Phenotypic Prediction and PhenotypeGenotype Mapping using Neural Networks.- 3D Plant Phenotyping: All You Need is Labelled Point Cloud Data.- Phenotyping problems of parts-per-object count.- Abiotic Stress Prediction from RGB-T Images of Banana Plantlets.- Sorghum Segmentation by Skeleton Extraction.- Towards Confirmable Automated Plant Cover Determination.- Unsupervised Domain Adaptation For Plant Organ Counting.- Automatic Differentiation of Damaged and Unharmed Grapes Using RGB Images and Convolutional Neural Networks.- Germination Detection of Seedlings in Soil: A System, Dataset and Challenge.- Detection in agricultural contexts: Are we close to human level.- AutoCount: Unsupervised Segmentation and Counting of Organs in Field Images.- CorNet: Unsupervised Deep Homography Estimation for Agricultural Aerial Imagery.- Expanding CNN-based Plant Phenotyping Systems to Larger Environments.- Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM.- BTWD: Bag of Tricks for Wheat Detection.- W41 - Fair Face Recognition and Analysis.- FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition.- AsArcFace: Asymmetric Additive Angular Margin Loss for Fairface Recognition.- Fair Face Recognition Using Data Balancing, Enhancement and Fusion.- Investigating Bias and Fairness in Facial Expression Recognition.- Disguised Face Verification using Inverse Disguise Quality.- W44 - Perception Through Structured Generative Models.- Toward Continuous-Time Representations of Human Motion.- DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors.- 3D Noise and Adversarial Supervision Is All You Need for Multi-Modal Semantic Image Synthesis.
