LEADER 06351nam 22007695 450 001 996587863403316 005 20240128103225.0 010 $a3-031-53305-4 024 7 $a10.1007/978-3-031-53305-1 035 $a(MiAaPQ)EBC31092425 035 $a(Au-PeEL)EBL31092425 035 $a(DE-He213)978-3-031-53305-1 035 $a(EXLCZ)9930114608300041 100 $a20240127d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMultiMedia Modeling$b[electronic resource] $e30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 ? February 2, 2024, Proceedings, Part I /$fedited by Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (523 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14554 311 08$aPrint version: Rudinac, Stevan MultiMedia Modeling Cham : Springer International Publishing AG,c2024 9783031533044 327 $aWhere are Biases? Adversarial Debiasing with Spurious Feature Visualization -- Cross-Modal Hash Retrieval with Category Semantics -- Spatiotemporal Representation Enhanced ViT for Video Recognition -- SCFormer: A Vision Transformer with Split Channel in Sitting Posture Recognition -- Dive into Coarse-to-Fine Strategy in Single Image Deblurring -- TICondition: Expanding Control Capabilities for Text-to-Image Generation with Multi-Modal Conditions -- Enhancing Generative Generalized Zero Shot Learning via Multi-Space Constraints and Adapative Integration -- Joint Image Data Hiding and Rate-Distortion Optimization in Neural Compressed Latent Representations -- GSUNet: A Brain Tumor Segmentation Method Based On 3D Ghost Shuffle U-Net -- ACT: Action-associated and Target-related Representations for Object Navigation -- Foreground Feature Enhancement and Peak & Background Suppression for Fine-Grained Visual Classification -- YOLOv5-SRR: Enhancing YOLOv5 for Effective Underwater Target Detection -- Image Clustering and Generation with HDGMVAE-I -- ?Car or Bus?" CLearSeg: CLIP-enhanced Discrimination among Resembling Classes for Few-Shot Semantic Segmentation -- PANDA: Prompt-based Context- and Indoor-aware Pretraining for Vision and Language Navigation -- Cross-Modal Semantic Alignment Learning for Text-based Person Search -- Point Cloud Classification via Learnable Memory Bank -- Adversarially Regularized Low-Light Image Enhancement -- Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation -- PMGCN:Preserving measuring mapping prototype graph calibration network for few-shot learning -- ARE-CAM: An interpretable approach to quantitatively evaluating the adversarial robustness of deep models based on CAM -- SSK-Yolo:Global feature-driven small object detection network for images -- MetaVSR: A Novel Approach to Video Super-Resolution for Arbitrary Magnification -- From Skulls to Faces: A Deep Generative Framework for Realistic 3D Craniofacial Reconstruction -- Structure-aware Adaptive Hybrid Interaction Modeling for Image-Text Matching -- Using Saliency and Cropping to Improve Video Memorability -- Contextual Augmentation with Bias Adaptive for Few-shot Video Object Segmentation -- A lightweight local attention network for image super resolution -- Domain Adaptation for Speaker Verification Based on Self-Supervised Learning with Adversarial Training -- Quality Scalable Video Coding based on Neural Representation -- Hierarchical Bi-Directional Temporal Context Mining for Improved Video Compression -- MAMixer: Multivariate Time Series Forecasting via Multi-Axis Mixing -- A Custom GAN-based Robust Algorithm for Medical Image Watermarking -- A Detail-guided Multi-source Fusion Network for Remote Sensing Object Detection -- A Secure and Fair Federated Learning Protocol under the Universal Composability Framework -- Bi-directional Interaction and Dense Aggregation Network for RGB-D Salient Object Detection -- Face Forgery Detection via Texture and Saliency Enhancement. 330 $aThis book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29 ? February 2, 2024. The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14554 606 $aComputer vision 606 $aImage processing 606 $aPattern recognition systems 606 $aApplication software 606 $aInformation storage and retrieval systems 606 $aMachine learning 606 $aComputer Vision 606 $aImage Processing 606 $aAutomated Pattern Recognition 606 $aComputer and Information Systems Applications 606 $aInformation Storage and Retrieval 606 $aMachine Learning 615 0$aComputer vision. 615 0$aImage processing. 615 0$aPattern recognition systems. 615 0$aApplication software. 615 0$aInformation storage and retrieval systems. 615 0$aMachine learning. 615 14$aComputer Vision. 615 24$aImage Processing. 615 24$aAutomated Pattern Recognition. 615 24$aComputer and Information Systems Applications. 615 24$aInformation Storage and Retrieval. 615 24$aMachine Learning. 676 $a006.37 700 $aRudinac$b Stevan$01591967 701 $aHanjalic$b Alan$01591968 701 $aLiem$b Cynthia$0861297 701 $aWorring$b Marcel$01591969 701 $aJónsson$b Bjö Þór$01591970 701 $aLiu$b Bei$01384492 701 $aYamakata$b Yoko$01382109 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996587863403316 996 $aMultiMedia Modeling$93907840 997 $aUNISA