Computer Vision Systems: 13th International Conference, ICVS 2021, Virtual Event, September 22-24, 2021, Proceedings

Preface
Organization
Contents
Attention Systems
Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields
	1 Introduction
	2 Second-Order Channel Attention with Varying Receptive Fields
		2.1 Second-Order Channel Attention
		2.2 Dilated Convolutions
		2.3 Compression Through Dilations
		2.4 Model Overview
	3 Experimental Results
		3.1 Datasets
		3.2 Implementation
		3.3 Evaluation
	4 Conclusion
	References
MARL: Multimodal Attentional Representation Learning for Disease Prediction
	1 Introduction
	2 Related Work
	3 Multimodal Attentional Representation Learning
		3.1 Preprocessing
		3.2 Lung Segmentation with Spatial Fuzzy C-Means
		3.3 Patient Biological Data Enrichment
		3.4 Multimodal Representation Learning
	4 Experimental Work
		4.1 IPF Lung Disease Dataset
		4.2 Regression of IPF Lung Disease Progression
		4.3 IPF Disease Status Classification
	5 Conclusion
	References
Object Localization with Attribute Preference Based on Top-Down Attention
	1 Introduction
	2 Related Work
	3 Architecture
		3.1 Deep Attribute Network
		3.2 Top-Down Attention
	4 Experiments
		4.1 Datasets
		4.2 Pointing Game Evaluation
		4.3 Experiment 1: Attribute Localization
		4.4 Experiment 2: Joint Attribute-Object Localization
	5 Conclusion
	References
See the Silence: Improving Visual-Only Voice Activity Detection by Optical Flow and RGB Fusion
	1 Introduction
	2 Related Work
	3 Our Approach
	4 Experimental Evaluation
		4.1 Dataset and Training
		4.2 Results
	5 Conclusion
	References
Classification and Detection
Score to Learn: A Comparative Analysis of Scoring Functions for Active Learning in Robotics
	1 Introduction
	2 Related Work
		2.1 Deep Learning Based Object Detection
		2.2 Weakly-Supervised Learning of Object Detection
	3 Methods
		3.1 Overview of the Pipeline
		3.2 Scoring Functions
	4 Experiments
		4.1 Experimental Setup
		4.2 Results Analysis on Pascal VOC
		4.3 Results Analysis on iCWT
	5 Discussion
	References
Enhancing the Performance of Image Classification Through Features Automatically Learned from Depth-Maps
	1 Introduction
	2 Literature Review on Indoor-Outdoor Image Classification
	3 Methodology
		3.1 Data Set
		3.2 Feature Extraction
		3.3 Unsupervised Learning-Based Analysis
		3.4 Supervised Learning Based Analysis
	4 Results and Discussion
		4.1 Experimental Setup
		4.2 Results of the Unsupervised Learning Based Analysis
		4.3 Results of the Supervised Learning Based Analysis
	5 Conclusions and Future Work
	References
Object Detection on TPU Accelerated Embedded Devices
	1 Introduction
	2 Related Works
		2.1 Mobile Object Detectors
		2.2 Embedded Deep Learning
	3 Methodology
		3.1 Framework and Quantization
		3.2 Datasets
		3.3 Transfer Learning
	4 Evaluation
		4.1 Inference Time
		4.2 Accuracy
		4.3 Versatility and Training Speed
		4.4 Overall Performance
	5 Conclusion
	References
Tackling Inter-class Similarity and Intra-class Variance for Microscopic Image-Based Classification
	1 Introduction
	2 Related Work
	3 Method
		3.1 Inter-class Similarity
		3.2 Intra-class Variance
		3.3 Training Algorithm
	4 Experiments
		4.1 Datasets
		4.2 Baselines
		4.3 Evaluation Metrics
		4.4 Implementation Details
	5 Results
		5.1 Diatom Dataset
		5.2 WHOI-Plankton Dataset
	6 Conclusion
	References
Semantic Interpretation
Measuring the Sim2Real Gap in 3D Object Classification for Different 3D Data Representation
	1 Introduction
	2 Related Work
		2.1 View-Based Representation
		2.2 Grid-Based Representation
		2.3 Point-Based Representation
	3 Measuring the Sim2Real Gap on ScanObjectNN
		3.1 Experimental Setup
		3.2 Results and Analysis
	4 Disentangling the Impact of Design Choices
		4.1 Hierarchical Learning from Object Parts
		4.2 Impact of Surface-Based or Euclidean-Based Representation
		4.3 Impact of Over- and Under-Segmentation and Scale
		4.4 Application-Specific Considerations
	5 Conclusion
	References
Spatially-Constrained Semantic Segmentation with Topological Maps and Visual Embeddings
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Topological Representation
		3.2 Structuring Vertices
		3.3 Spatial Segmentation
		3.4 Semantic Segmentation
	4 Experimental Results
	5 Conclusion and Future Work
	References
Knowledge-Enabled Generation of Semantically Annotated Image Sequences of Manipulation Activities from VR Demonstrations
	1 Introduction
	2 Overview
		2.1 Virtual Environment
		2.2 Recorded Episodes
	3 Data Collection
		3.1 Episode Replay
		3.2 3D Sphere Scan
	4 Experiments
	5 Related Work
	6 Conclusion and Future Work
	References
Make It Easier: An Empirical Simplification of a Deep 3D Segmentation Network for Human Body Parts
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Annotation Algorithm
		3.2 Segmentation Algorithm
	4 Experiments
		4.1 Model Selection
		4.2 Data Augmentation
		4.3 Cross-Validation
	5 Conclusion
	References
Video and Motion Analysis
Video Popularity Prediction Through Fusing Early Viewership with Video Content
	1 Introduction
	2 Related Work
	3 Proposed Video Popularity Prediction Approach
	4 Experimental Results
		4.1 Datasets
		4.2 Evaluation
	5 Conclusion
	References
Action Prediction During Human-Object Interaction Based on DTW and Early Fusion of Human and Object Representations
	1 Introduction
	2 Related Work
	3 DTW-Based Action Prediction
		3.1 Feature Extraction
		3.2 DTW-Based Time Series Alignment
		3.3 Early Fusion of Human and Object Representations
	4 Experiments
	5 Summary
	References
GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids
	1 Introduction
	2 Related Work
	3 Method
		3.1 Bayesian Occupancy Grids
		3.2 Semantic Grid
		3.3 3D Object Detection
		3.4 Grid Tracking Network
		3.5 Association
		3.6 Training
	4 Experiments
		4.1 Qualitative Results
		4.2 Quantitative Results
	5 Conclusion
	References
An Efficient Video Desnowing and Deraining Method with a Novel Variant Dataset
	1 Introduction
	2 Related Works
		2.1 Image-Based Snow/Rain Removal
		2.2 Video-Based Snow/Rain Removal
	3 Dataset Development
		3.1 Videos with Synthetic Snow and Synthetic Rain
		3.2 Videos with Quasi-snow
		3.3 Videos with Real Snow and Rain
	4 Proposed Method
	5 Experimental Results and Comparison
		5.1 Performance Evaluation
		5.2 Failure Cases
	6 Conclusion
	References
Computer Vision Systems in Agriculture
Robust Counting of Soft Fruit Through Occlusions with Re-identification
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Tracking
		3.2 Re-identification and Class Description Network
		3.3 Tracking Sequences
		3.4 Evaluation Metrics
	4 Results
	5 Conclusion
	References
Non-destructive Soft Fruit Mass and Volume Estimation for Phenotyping in Horticulture
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Volume Estimation
		3.2 Mass Estimation
	4 Experiments and Results
		4.1 Data Collection
		4.2 Phenotypic Trait Predictions
		4.3 In-Field Experiments
	5 Discussion
	6 Conclusions and Future Work
	References
Learning Image-Based Contaminant Detection in Wool Fleece from Noisy Annotations
	1 Introduction
	2 Related Work
		2.1 Contaminant Detection in Wool
		2.2 Semantic Segmentation
	3 Semantic Segmentation from Noisy Annotations
		3.1 Problem Definition
		3.2 Learning Probabilistic Output
	4 Wool Datasets
	5 Experiments
		5.1 Implementation Details
		5.2 Results and Discussion
	6 Conclusion
	References
Active Learning for Crop-Weed Discrimination by Image Classification from Convolutional Neural Network\'s Feature Pyramid Levels
	1 Introduction
	2 Literature Review
		2.1 Robotic Weeding
		2.2 Active Learning
		2.3 Convolutional Neural Networks and Features Pyramid Network
	3 Proposed Method
		3.1 Workflow Description
		3.2 Model Training Setup
	4 Experimental Setup
	5 Experimental Evaluation
	6 Conclusions and Future Work
	References
Author Index