Computational Visual Media

Name: Computational Visual Media | 12th International Conference, CVM 2024, Wellington, New Zealand, April 10-12, 2024, Proceedings, Part II
Brand: Springer
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12th International Conference, CVM 2024, Wellington, New Zealand, April 10-12, 2024, Proceedings, Part II

Fang-Lue Zhang Andrei Sharf(Editor)

Springer (Publisher)

Published on 29. March 2024

XIV, 377 pages

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978-981-97-2092-7 (ISBN)

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Content

Intro
Preface
Organization
Contents - Part II
Contents - Part I
Facial Images
Zero-Shot Real Facial Attribute Separation and Transfer at Novel Views
1 Introduction
2 Related Works
2.1 Explicit Face Morphable Models
2.2 3D-Aware Implicit Models
2.3 Disentanglement Representation Learning
3 Method
3.1 Model Architecture
3.2 EM-Like Alternating Training Procedure
3.3 Model Parameters Initialization
3.4 Rendering Refinement with Blind Face Restoration
4 Experiment
4.1 Implementation Details
4.2 Zero-Shot Attribute Separation from Single Image
4.3 Comparisons
4.4 Ablation Study
5 Conclusion
5.1 Limitation
References
Explore and Enhance the Generalization of Anomaly DeepFake Detection
1 Introduction
2 Related Work
2.1 Conventional DeepFake Detection
2.2 Anomaly DeepFake Detection
3 Approach
3.1 Overview
3.2 Review and Exploration of ADFD
3.3 Boundary Blur Mask Generator
3.4 Noise Refinement Strategy
3.5 Algorithm
4 Experiments
4.1 Experiments Setting
4.2 Exploration Experiments of ADFD Methods
4.3 Comparison Experiments
5 Conclusion
References
Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment
1 Introduction
2 Related Work
2.1 Image Quality Assessment
2.2 Face Image Quality Assessment
3 Method
3.1 Recognition-Oriented Non-reference Quality Measurement
3.2 Tiny Face Quality Network
3.3 Generating Training Dataset with Quality Labels
3.4 Data Sampling and Augmentation Strategy for Balancing the Distribution of Scores
4 Experimental Results
4.1 Experimental Setup
4.2 Datasets and Protocols
4.3 Visualization of Different FIQA Methods
4.4 Memory and Computation Costs
4.5 Quantitative Evaluation on IJB-B and IJB-C Datasets
4.6 Quantitative Evaluation on YTF Dataset
4.7 Ablation Studies
5 Conclusion
References
Face Expression Recognition via Product-Cross Dual Attention and Neutral-Aware Anchor Loss
1 Introduction
2 Related Work
2.1 Landmark
2.2 Transformer in FER
2.3 Losses Used in FER
3 Our Method
3.1 Product-Cross Dual Attention Module
3.2 Neutral Expression Aware Anchor Loss
3.3 Total Loss Function
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Ablation Study
4.4 Comparison with the State-of-the-Art Methods
4.5 Comparison on Number of Parameters and Running Performance
5 Conclusion
References
Image Generation and Enhancement
Deformable CNN with Position Encoding for Arbitrary-Scale Super-Resolution
1 Introduction
2 Related Work
2.1 Implicit Neural Representation
2.2 Single Image Super-Resolution (SISR)
2.3 Arbitrary-Scale Super-Resolution
3 Methods
3.1 Deformable Feature Unfolding (DFU)
3.2 Fusion with Learned Position Encoding (FPE)
3.3 Deep ResMLP
4 Experiments
4.1 Datasets and Metrics
4.2 Implementation Detail
4.3 Evaluation
4.4 Ablation Study
5 Conclusion
References
Single-Video Temporal Consistency Enhancement with Rolling Guidance
1 Introduction
2 Related Work
2.1 Temporal Consistency for Specific Tasks
2.2 Blind Video Temporal Consistency
2.3 Spatial Smoothing Filters and Rolling Guidance
3 Method
3.1 Overview
3.2 Constructing Coarse Guidance Video
3.3 Recovering Image Details
3.4 Global Refinement
3.5 Comparison with the Deflickering Algorithm
4 Experiment
4.1 Dataset
4.2 Quality Assessment
4.3 Comparison to State-of-the-Art Methods
4.4 Ablation Study
5 Discussion and Conclusion
References
GTLayout: Learning General Trees for Structured Grid Layout Generation
1 Introduction
2 Related Work
3 Method
3.1 Structural Layout Representation
3.2 Generative Model for Structured Grid Layouts
3.3 Training
4 Evaluation
4.1 Layout Generation
4.2 Layout Reconstruction
4.3 Layout Interpolation
5 Conclusion
References
Image Understanding
Silhouette-Based 6D Object Pose Estimation
1 Introduction
2 Related Work
2.1 Traditional Methods
2.2 Methods with Deep Learning
3 The Method
3.1 Problem Formulation and Notation
3.2 Dimensionality Reduction
3.3 Optimized Particle Swarm Optimization
4 Experiments
4.1 Experiments Setup
4.2 Comparison to State of the Art
4.3 Performance on YCB-V-NT and TR-RW
4.4 Silhouette Stability Experiments
4.5 Ablation Study on YCB-V
5 Conclusion and Outlook
References
Robust Light Field Depth Estimation over Occluded and Specular Regions
1 Introduction
2 Related Work
3 The Depth Estimation
3.1 Consistency Data and Confidence
3.2 NPCR Depth Estimation
3.3 Depth Refinement
4 Experiment
4.1 Occlusion Processing Comparisons
4.2 Specular Regions Processing
4.3 Depth Map
4.4 Computational Time
5 Conclusion and Limitation
References
Foreground and Background Separate Adaptive Equilibrium Gradients Loss for Long-Tail Object Detection
1 Introduction
2 Related Works
2.1 General Object Detection
2.2 Long-Tail Object Detection
3 Methodology
3.1 Revisiting Sigmoid Cross-Entropy Loss
3.2 Foreground and Background Separate Adaptive Equilibrium Gradients Loss
4 Experiments on LVIS
4.1 Datasets and Evaluation Metric
4.2 Implementation Details
4.3 Ablation Studies
4.4 Generalization on Stronger Models
4.5 Performance Analysis
4.6 Comparison with State-of-the-Art Methods
4.7 Evaluation on COCO-LT
4.8 Result Visualization
5 Conclusion
References
Stylization
Multi-level Patch Transformer for Style Transfer with Single Reference Image
1 Introduction
2 Related Work
3 Methodology
3.1 Multi-level Patch Transformer Encoder
3.2 Dynamic Filter-Based Decoder
3.3 Loss Functions
4 Experiments and Evaluations
4.1 Implementation Details
4.2 Qualitative Evaluation
4.3 Ablation Study
4.4 User Study
4.5 Quantitative Evaluations
4.6 Discussion CycleTransformer vs CycleGAN
5 Conclusion and Future Work
References
Palette-Based Content-Aware Image Recoloring
1 Introduction
2 Related Works
2.1 Palette-Based Image Recoloring
2.2 Edit Propagation (Stroke-Based Image Recoloring)
2.3 Style Transfer (Example-Based Image Recoloring)
3 Method
3.1 Overview
3.2 Palette Extraction
3.3 Content-Aware Recoloring
4 Experiments
4.1 Results
4.2 Evaluation
4.3 Comparisons
5 Conclusion, Limitation and Future Work
References
FreeStyler: A Free-Form Stylization Method via Multimodal Vector Quantization
1 Introduction
2 Related Work
3 Method
3.1 Vector Quantization Framework
3.2 Pseudo-Paired Token Predictor
4 Experiments
4.1 Implementation Details
4.2 Qualitative Results
4.3 Quantitative Results
4.4 Ablation Study
4.5 Applications
5 Limitations and Future Work
6 Conclusion
References
Vision Meets Graphics
Denoised Dual-Level Contrastive Network for Weakly-Supervised Temporal Sentence Grounding
1 Introduction
2 Related Work
2.1 Weakly-Supervised Temporal Sentence Grounding
2.2 Contrastive Representation Learning
3 The Proposed Method
3.1 Problem Formulation
3.2 Visual-Text Feature Extraction
3.3 Gaussian-Based Proposal Generation
3.4 Intra-video Contrastive Learning
3.5 Inter-video Contrastive Learning
3.6 Pseudo-Label Noise Removal
3.7 Training and Inference
4 Experiments
4.1 Datasets
4.2 Evaluation Metric
4.3 Implementation Details
4.4 Comparisons with State-of-the-Art Methods
4.5 Ablation Study and Analysis
4.6 Qualitative Results
5 Conclusion
References
Isolation and Integration: A Strong Pre-trained Model-Based Paradigm for Class-Incremental Learning
1 Introduction
2 Realeated Work
3 Method
3.1 Problem Setting
3.2 A Simple Baseline
3.3 Dynamically Adaption and Aggregation
4 Experiments
4.1 Experimental Setups
4.2 Comparison with State of the Art
4.3 Ablation Study
5 Conclusion
References
Object Category-Based Visual Dialog for Effective Question Generation
1 Introduction
2 Related Work
3 Model
3.1 Object Information Extraction
3.2 Category Selection
3.3 Object Fusion Feature Update
3.4 Object-Self Difference Attention Module
3.5 Question Decoder
3.6 Object-Level Attention Update
4 Experiments
4.1 Dataset
4.2 Evaluation Metrics
4.3 Experiment Settings
4.4 Results
5 Conclusions
References
AST: An Attention-Guided Segment Transformer for Drone-Based Cross-View Geo-Localization
1 Introduction
2 Related Work
2.1 Image-Based Cross-View Geo-Localization
2.2 Vision Transformer
3 Proposed Method
3.1 Problem Formulation
3.2 Vision Transformer for Cross-View Geo-Localization
3.3 Attention-Guided Segment Tokens
3.4 Loss Function and Training Strategy
4 Experiment
4.1 Datasets and Evaluation Metrics
4.2 Implementation Details
4.3 Comparison with Existing Methods
4.4 Ablation Study
4.5 Visualization
5 Conclusion
References
Improved YOLOv5 Algorithm for Small Object Detection in Drone Images
1 Introduction
2 Related Work
2.1 Object Detection
2.2 Small Object Detection
2.3 YOLOv5
3 HTH-YOLOv5
3.1 Hybrid Transformer Head
3.2 Convolutional Attention Feature Fusion Module
3.3 CAH-Transformer Module
4 Experiment
4.1 Data Sets and Evaluation Metrics
4.2 Comparison with Existing Methods
4.3 Ablation Experiment
4.4 Experimental Analysis of COCO Dataset
4.5 Algorithm Effectiveness Analysis
5 Conclusion
References
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Computational Visual Media

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