PRICAI 2021 : trends in artificial intelligence : 18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021, Hanoi, Vietnam, November 8-12, 2021 : proceedings. Part III

PRICAI 2021 : trends in artificial intelligence : Part III / 18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021, Hanoi, Vietnam, November 8-12, 2021 : proceedings. Duc Nghia Pham, Thanaruk Theeramunkong, Guido Governatori, Fenrong Liu (eds.).

This three-volume set, LNAI 13031, LNAI 13032, and LNAI 13033 constitutes the thoroughly refereed proceedings of the 18th Pacific Rim Conference on Artificial Intelligence, PRICAI 2021, held in Hanoi, Vietnam, in November 2021. The 93 full papers and 28 short papers presented in these volumes were c...

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Bibliographic Details
Corporate Author:	Pacific Rim International Conference on Artificial Intelligence Online
Other Authors:	Pham, Duc-Nghia (Editor), Theeramunkong, Thanaruk (Editor), Governatori, Guido (Editor), Liu, Fenrong (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer, [2021]
Series:	Lecture notes in computer science. Lecture notes in artificial intelligence. Lecture notes in computer science ; 13033. LNCS sublibrary. Artificial intelligence.
Subjects:	Artificial intelligence > Congresses. Artificial intelligence Electronic books. proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès.
Online Access:	Click for online access

Table of Contents:

Intro
Preface
Organization
Contents
Part III
Reinforcement Learning
Consistency Regularization for Ensemble Model Based Reinforcement Learning
1 Introduction
2 Related Work
3 Background
4 Method
4.1 Model Discrepancy and Consistency
4.2 Model Learning
4.3 Implementation
5 Experiments
5.1 Comparative Evaluation
5.2 Effects of Consistency Regularization
5.3 Ablation Study
6 Conclusions
References
Detecting and Learning Against Unknown Opponents for Automated Negotiations
1 Introduction
2 Related Work
3 Preliminaries
3.1 Negotiation Settings
3.2 Bayes Policy Reuse
4 Agent Design
4.1 Deep Reinforcement Learning Based Learning Module
4.2 Policy Reuse Mechanism
5 Experiments
5.1 Experimental Setup
5.2 Performance Against ANAC Winning Agents
5.3 New Opponent Detection and Learning
6 Conclusion
References
Diversity-Based Trajectory and Goal Selection with Hindsight Experience Replay
1 Introduction
2 Background
2.1 Reinforcement Learning
2.2 Goal-Oriented Reinforcement Learning
2.3 Deep Deterministic Policy Gradient
2.4 Determinantal Point Processes
3 Related Work
4 Methodology
4.1 Diversity-Based Trajectory Selection
4.2 Diversity-Based Goal Selection
5 Experiments
5.1 Environments
5.2 Training Settings
5.3 Benchmark Results
5.4 Ablation Studies
5.5 Time Complexity
6 Conclusion
References
Off-Policy Training for Truncated TD() Boosted Soft Actor-Critic
1 Introduction
2 Related Work
2.1 TD Learning and Multi-step Methods
2.2 TD() and Eligibility Traces
3 Preliminaries
3.1 MDPs and Temporal Difference Learning
3.2 Multi-step Algorithms and TD()
4 Soft Actor-Critic with Truncated TD ()
4.1 Off-Policy Truncated TD()
4.2 Soft Actor-Critic with Truncated TD().
4.3 SAC() Training
5 Experiments
5.1 Evaluation of SAC()
5.2 Ablation Study
6 Discussion
References
Adaptive Warm-Start MCTS in AlphaZero-Like Deep Reinforcement Learning
1 Introduction
2 Related Work
3 Warm-Start AlphaZero Self-play
3.1 The Algorithm Framework
3.2 MCTS
3.3 MCTS Enhancements
4 Adaptive Warm-Start Switch Method
5 Experimental Setup
6 Results
6.1 MCTS Vs MCTS Enhancements
6.2 Fixed I Tuning
6.3 Adaptive Warm-Start Switch
7 Discussion and Conclusion
References
Batch-Constraint Inverse Reinforcement Learning
1 Introduction
2 Offline Inverse Reinforcement Learning
3 Method
3.1 Feature Expectation Approximation
3.2 Policy Optimization with BRL
3.3 Batch-Constraint Inverse Reinforcement Learning Algorithm (BCIRL)
4 Experiments
4.1 Standard Control Environments
4.2 Gridworld Example
5 Conclusion
References
KG-RL: A Knowledge-Guided Reinforcement Learning for Massive Battle Games
1 Introduction
2 Related Work
3 Method
3.1 Rule-Mix
3.2 Plan-Extend
4 Experiment Setup
4.1 Environment
4.2 Human Knowledge Based Module Design
4.3 Experiment Settings
5 Experimental Results
5.1 Battle Game
5.2 Comparison of Training Process
5.3 Model Differences
5.4 The Influence of Different Decisions and Action Modules
5.5 Discussion
6 Conclusion
References
Vision and Perception
A Semi-supervised Defect Detection Method Based on Image Inpainting
1 Introduction
2 Related Work
3 Methodology
3.1 Architecture
3.2 Loss Function
4 Experiments
4.1 Preparations
4.2 Implementation Details
4.3 Results
5 Conclusions
References
ANF: Attention-Based Noise Filtering Strategy for Unsupervised Few-Shot Classification
1 Introduction
2 Related Work
3 Approach
3.1 Dictionary Noises.
3.2 Direct Noise Filter
3.3 Attention-Based Noise Filter
3.4 Dynamic Momentum Updating
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Experimental Results
4.4 Visualization of Filter Results
4.5 Ablation Studies
4.6 Traditional Feature Descriptor
5 Conclusions
References
Asymmetric Mutual Learning for Unsupervised Cross-Domain Person Re-identification
1 Introduction
2 Related Work
3 Proposed Method
3.1 Structure of Asymmetric Mutual Learning
3.2 Merging Clusters Algorithm
3.3 Similarity Weighted Loss
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Comparison with State-of-the-Art Methods
4.4 Ablation Study
5 Conclusion
References
Collaborative Positional-Motion Excitation Module for Efficient Action Recognition
1 Introduction
2 Related Work
2.1 Action Recognition
2.2 CNN-Based Approaches
2.3 Temporal Modeling in Action Recognition
2.4 Attention Mechanisms
3 Approach
3.1 Architecture of CPME
3.2 CPME Network
4 Experiments
4.1 Experimental Settings
4.2 Implementation Details
4.3 Improving the Baseline 2D CNN-Approach
4.4 Comparison with the State of the Art
5 Conclusion
References
Graph Attention Convolutional Network with Motion Tempo Enhancement for Skeleton-Based Action Recognition
1 Introduction
2 Related Work
2.1 GCN for Skeleton Action Recognition
2.2 Motion Tempo Modeling
3 Method
3.1 Multi-neighborhood Graph Attention Module
3.2 Motion Tempo Modeling
4 Experiments
4.1 Datasets
4.2 Training Details
4.3 Ablation Study
4.4 Comparisons with the State-of-the-Art Methods
5 Conclusion
References
Learning to Synthesize and Remove Rain Unsupervisedly
1 Introduction
2 Related Work
2.1 Single Image Deraining Methods
2.2 Rain Synthesis Methods.
2.3 Generative Adversarial Networks
3 SAA-CycleGAN
3.1 Overview
3.2 Deraining Process
3.3 Rain Synthesis Process
3.4 Objective Function
4 Experimental Results
4.1 Implementation Details
4.2 Rain Synthesis Results
4.3 Deraining Results
4.4 Ablation Study
5 Conclusion
References
Object Bounding Box-Aware Embedding for Point Cloud Instance Segmentation
1 Introduction
2 Related Work
2.1 Deep Learning Methods on Point Cloud
2.2 Instance Segmentation on Point Cloud
3 Method
3.1 Network Framework
3.2 Bounding Box Prediction Branch
3.3 Instance Segmentation Branch
4 Experiments
4.1 Experiment Settings
4.2 Ablation Study
4.3 Comparison with State-of-the-Art Approaches
5 Conclusion
References
Objects as Extreme Points
1 Introduction
1.1 Key-Point-Based Prediction
1.2 Dense Prediction
1.3 Motivation
2 Related Work
2.1 Anchor-Free Object Detection
2.2 Localization and Classification Spatial Misalignment
2.3 Regression Loss
3 Method
3.1 Positive Sampling with Dynamic Radius
3.2 Network Outputs
3.3 EIoU Loss
3.4 EIoU Predictor
3.5 Optimization
4 Experiments
4.1 Implementation Details
4.2 Ablation Study
4.3 State-of-the-Art Comparisons
5 Conclusion
References
Occlusion-Aware Facial Expression Recognition Based Region Re-weight Network
1 Introduction
2 Related Work
2.1 FER Methods Against Occlusions
2.2 Sparse Representation
3 Proposed Method
3.1 Overview of Region Re-weight Network
3.2 Occlusion-Aware Module
3.3 Block-Loss Module
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Visualization of the Blocks Selected by OAM
4.4 Ablation Studies Evaluation
4.5 Results and Comparison
5 Conclusion
References.
Online Multi-Object Tracking with Pose-Guided Object Location and Dual Self-Attention Network
1 Introduction
2 Related Work
3 Proposed Method
3.1 Soft-Pose-NMS Object Detection Strategy
3.2 Feature Extraction with Dual Self-Attention Network
3.3 Data Association and Trajectory Management
4 Experiments
4.1 Implementation Details
4.2 Performance on MOT Benchmark Datasets
4.3 Ablation Studies
5 Conclusions
References
Random Walk Erasing with Attention Calibration for Action Recognition
1 Introduction
2 Related Work
2.1 Video Action Recognition
2.2 Motion Occlusion in Video
3 Approach
3.1 Network Overview
3.2 Random Walk Erasing Module
3.3 Attention Calibration Module
4 Experiments
4.1 Datasets and Implementations
4.2 Main Results
4.3 Ablation Studies
5 Conclusion
References
RGB-D Based Visual Navigation Using Direction Estimation Module
1 Introduction
2 Related Works
3 Method
3.1 Task Definition
3.2 3D Geometry
3.3 Visual and Spatial Features of Objects
3.4 Direction Estimation Module
3.5 Actor-Critic Policy Network
4 Experiment
4.1 Dataset and Evaluation
4.2 Experiment Setup and Comparison Methods
4.3 Training Details
4.4 Results and Analysis
4.5 Ablation Study
5 Conclusion
References
Semi-supervised Single Image Deraining with Discrete Wavelet Transform
1 Introduction
2 Related Works
3 Semi-supervised Image Deraining by DWT
3.1 Methodology Overview
3.2 Residual Attentive Network Architecture
3.3 Discriminator by DWT for Semi-supervised Method
4 Experimental Results
4.1 Datasets and Measurements
4.2 Implementation Details
4.3 Results and Analysis
4.4 Ablation Study
5 Conclusion
References
Simple Light-Weight Network for Human Pose Estimation
1 Introduction
2 Methodology.

PRICAI 2021 : trends in artificial intelligence : Part III / 18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021, Hanoi, Vietnam, November 8-12, 2021 : proceedings. Duc Nghia Pham, Thanaruk Theeramunkong, Guido Governatori, Fenrong Liu (eds.).

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