Buch, Englisch, 522 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 809 g
30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 - February 2, 2024, Proceedings, Part II
Buch, Englisch, 522 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 809 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-031-53307-5
Verlag: Springer Nature Switzerland
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.Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
Weitere Infos & Material
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 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.
