MultiMedia Modeling
30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 - February 2, 2024, Proceedings, Part II
(Sprache: Englisch)
This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29-February 2, 2024.The 112 full papers included in this volume were carefully...
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Klappentext zu „MultiMedia Modeling “
This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29-February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.
Inhaltsverzeichnis zu „MultiMedia Modeling “
Self-distillation Enhanced Vertical Wavelet Spatial Attention for Person Re-identification.- High Capacity Reversible Data Hiding in Encrypted Images Based onPixel Value Preprocessing and Block Classification.- HPattack: An Effective Adversarial Attack for Human Parsing.- Dynamic-Static Graph Convolutional Network for Video-Based Facial Expression Recognition.- Hierarchical Supervised Contrastive Learning for Multimodal Sentiment Analysis.- Semantic Importance-Based Deep Image Compression Using A Generative Approach.- Drive-CLIP: Cross-modal Contrastive Safety-Critical Driving Scenario Representation Learning and Zero-shot Driving Risk Analysis.- MRHF: Multi-stage Retrieval and Hierarchical Fusion for Textbook Question Answering.- Multi-scale Decomposition Dehazing with Polarimetric Vision.- CLF-Net: A Few-shot Cross-Language Font Generation Method.- Multi-dimensional Fusion and Consistency for Semi-supervised Medical Image Segmentation.- Audio-Visual Segmentation By Leveraging Multi-Scaled Features Learning.- Multi-head Hashing with Orthogonal Decomposition for Cross-modal Retrieval.- Fusion Boundary and Gradient Enhancement Network for Camouflage Object Detection.- Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas.- SM-GAN: Single-stage and Multi-object Text Guided Image Editing.- MAVAR-SE: Multi-scale Audio-Visual Association Representation Network for End-to-end Speaker Extraction.- NearbyPatchCL: Leveraging Nearby Patches for Self-Supervised Patch-Level Multi-Class Classification in Whole-Slide Images.- Improving Small License Plate Detection with Bidirectional Vehicle-plate Relation.- A Purified Stacking Ensemble Framework for Cytology Classification.- SEAS-Net: Segment Exchange Augmentation for Semi-Supervised Brain Tumor Segmentation.- Super-Resolution-Assisted Feature Refined
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Extraction for Small Objects in Remote Sensing Images.- Lightweight Image Captioning Model Based on Knowledge Distillation.- Irregular License Plate Recognition via Global Information Integration.- TNT-Net: Point Cloud Completion by Transformer in Transformer.- Fourier Transformer for Joint Super-Resolution and Reconstruction ofMr Image.- MVD-NeRF: Resolving Shape-Radiance Ambiguity via Mitigating View Dependency.- DPM-Det: Diffusion Model Object Detection Based on DPM-Solver++Guided Sampling.- CT-MVSNet: Efficient Multi-View Stereo with Cross-scale Transformer.- A Coarse and Fine Grained Masking Approach for Video-groundedDialogue.- Deep self-supervised subspace clustering with triple loss.- LigCDnet:Remote Sensing Image Cloud Detection Based on Lightweight Framework.- Gait Recognition Based on Temporal Gait Information Enhancing.- Learning Complementary Instance Representation with Parallel Adaptive Graph-Based Network for Action Detection.- CESegNet:Context-Enhancement Semantic Segmentation NetworkBased on Transformer.- MoCap-Video Data Retrieval with Deep Cross-Modal Learning.- LRATNet: Local-Relationship-Aware Transformer Network for TableStructure Recognition.
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Bibliographische Angaben
- 2024, 1st ed. 2024, XVIII, 522 Seiten, 185 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata
- Verlag: Springer, Berlin
- ISBN-10: 3031533070
- ISBN-13: 9783031533075
Sprache:
Englisch
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