| Description |
1 online resource (xiv, 523 pages) : illustrations (some color) |
| Series |
Lecture notes in computer science, 1611-3349 ; 14436 |
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Lecture notes in computer science ; 14436. 1611-3349
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| Contents |
Intro -- Preface -- Organization -- Contents - Part XII -- Object Detection, Tracking and Identification -- OKGR: Occluded Keypoint Generation and Refinement for 3D Object Detection -- 1 Introduction -- 2 Related Works -- 2.1 LiDAR-Based 3D Object Detection -- 2.2 Object Shape Completion -- 3 Methodology -- 3.1 Overview -- 3.2 Occluded Keypoint Generation -- 3.3 Occluded Keypoint Refinement -- 3.4 Loss Function -- 4 Experiments -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Evaluation on KITTI Dataset -- 4.4 Evaluation on Waymo Open Dataset -- 4.5 Model Efficiency |
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4.6 Ablation Studies -- 5 Conclusion -- References -- Camouflaged Object Segmentation Based on Fractional Edge Perception -- 1 Introduction -- 2 Related Work -- 3 Interactive Task Learning Network -- 3.1 Integral and Fractional Edge -- 3.2 Camouflaged Edge Detection Module -- 4 Performance Evaluation -- 4.1 Datasets and Experiment Settings -- 4.2 Quantitative Evaluation -- 4.3 Qualitative Evaluation -- 4.4 Generalization of Edge Detection -- 5 Conclusion -- References -- DecTrans: Person Re-identification with Multifaceted Part Features via Decomposed Transformer -- 1 Introduction |
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2 Related Work -- 3 Methodology -- 3.1 Vision Transformer as Feature Extractor -- 3.2 Token Decomposition (TD) Layer -- 3.3 Data Augmentation for TD Layer -- 3.4 Training and Inference -- 4 Experiments -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Comparisons to State-of-the-arts -- 4.4 Ablation Study -- 5 Conclusion -- References -- AHT: A Novel Aggregation Hyper-transformer for Few-Shot Object Detection -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection -- 2.2 Hypernetworks -- 3 Method -- 3.1 Preliminaries -- 3.2 Overview -- 3.3 Dynamic Aggregation Module |
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3.4 Conditional Adaptation Hypernetworks -- 3.5 The Classification-Regression Detection Head -- 4 Experiments -- 4.1 Experimental Setting -- 4.2 Comparison Results -- 4.3 Ablation Study -- 4.4 Visualization of Our Module -- 5 Conclusion -- References -- Feature Refinement from Multiple Perspectives for High Performance Salient Object Detection -- 1 Introduction -- 2 Proposed Method -- 2.1 Overall Architecture -- 2.2 Attention-Guided Bi-directional Feature Refinement Module -- 2.3 Serial Atrous Fusion Module -- 2.4 Upsampling Feature Refinement Module -- 2.5 Objective Function -- 3 Experiments |
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3.1 Experimental Setup -- 3.2 Comparison with State-of-the-Art Methods -- 3.3 Ablation Study -- 4 Conclusion -- References -- Feature Disentanglement and Adaptive Fusion for Improving Multi-modal Tracking -- 1 Introduction -- 2 Related Work -- 2.1 Multi-modal Tracking -- 2.2 Transformers Tracking -- 3 Methodology -- 3.1 Preliminary -- 3.2 Our Approach -- 3.3 Training and Inference -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Comparison with State-of-the-Arts Multi-modal Trackers -- 4.3 Ablation Study -- 5 Conclusion -- References |
| Summary |
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis |
| Notes |
Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed January 5, 2024) |
| Subject |
Computer vision -- Congresses
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Pattern recognition systems -- Congresses
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| Genre/Form |
Electronic books
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| Form |
Electronic book
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| Author |
Liu, Qingshan (Computer scientist), editor.
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Wang, Hanzi, editor.
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Ma, Zhanyu, editor.
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Zheng, Weishi, editor.
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Zha, Hongbin, editor.
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Chen, Xilin, editor.
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Wang, Liang, editor
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Ji, Rongrong, 1983- editor.
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| ISBN |
9789819985555 |
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9819985552 |
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