Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXXVI / / edited by Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol

• Autore: Leonardis Aleš
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (581 pages)
• Disciplina: 006
• Soggetto topico: Image processing - Digital techniques; Computer vision; Image processing; Computer networks; Machine learning; Computers, Special purpose; User interfaces (Computer systems); Human-computer interaction; Computer Imaging, Vision, Pattern Recognition and Graphics; Image Processing; Computer Communication Networks; Machine Learning; Special Purpose and Application-Based Systems; User Interfaces and Human Computer Interaction
• Altri autori: RicciElisa RothȘtefan RussakovskyOlga SattlerTorsten VarolGül
• Nota di contenuto: InstructIR: High-Quality Image Restoration Following Human Instructions -- Asynchronous Large Language Model Enhanced Planner for Autonomous Driving -- Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation -- LayoutFlow: Flow Matching for Layout Generation -- Making Large Language Models Better Planners with Reasoning-Decision Alignment -- R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detection -- Representation Enhancement-Stabilization: Reducing Bias-Variance of Domain Generalization -- Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify Inference -- An Optimization Framework to Enforce Multi-View Consistency for Texturing 3D Meshes -- STAG4D: Spatial-Temporal Anchored Generative 4D Gaussians -- RGBD GS-ICP SLAM -- Efficient NeRF Optimization - Not All Samples Remain Equally Hard -- Revisiting Calibration of Wide-Angle Radially Symmetric Cameras -- Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs -- Robust Incremental Structure-from-Motion with Hybrid Features -- Revisiting Domain-Adaptive Object Detection in Adverse Weather by the Generation and Composition of High-Quality Pseudo-Labels -- Prediction Exposes Your Face: Black-box Model Inversion via Prediction Alignment -- Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion Models -- UniCal: Unified Neural Sensor Calibration -- Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models -- Urban Waterlogging Detection: A Challenging Benchmark and Large-Small Model Co-Adapter -- Pseudo-Embedding for Generalized Few-Shot Point Cloud Segmentation -- WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering -- ReMoS: 3D Motion-Conditioned Reaction Synthesis for Two-Person Interactions -- Statewide Visual Geolocalization in the Wild -- Any2Point: Empowering Any-modality Transformers for Efficient 3D Understanding -- Trajectory-aligned Space-time Tokens for Few-shot Action Recognition.
• Sommario/riassunto: The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
• Titolo autorizzato: Computer Vision – ECCV 2024
• ISBN: 3-031-72764-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910983389803321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 15094