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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXIV / edited by Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol.
Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online
View online- Format:
- Book
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 15082
- Language:
- English
- Subjects (All):
- Image processing--Digital techniques.
- Image processing.
- Computer vision.
- 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.
- Local Subjects:
- 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.
- Physical Description:
- 1 online resource (LXXXV, 507 p. 168 illus., 166 illus. in color.)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
- Summary:
- 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.
- Contents:
- Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning
- Improving Knowledge Distillation via Regularizing Feature Direction and Norm
- 3DFG-PIFu: 3D Feature Grids for Human Digitization from Sparse Views
- Lazy Diffusion Transformer for Interactive Image Editing
- Non-parametric Sensor Noise Modeling and Synthesis
- Stripe Observation Guided Inference Cost-free Attention Mechanism
- The Nerfect Match: Exploring NeRF Features for Visual Localization
- ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidance
- Robust Calibration of Large Vision-Language Adapters
- Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation
- Improving Domain Generalization in Self-Supervised Monocular Depth Estimation via Stabilized Adversarial Training
- milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing
- denoiSplit: a method for joint microscopy image splitting and unsupervised denoising
- AugDETR: Improving Multi-scale Learning for Detection Transformer
- Spherical World-Locking for Audio-Visual Localization in Egocentric Videos
- SPIN: Hierarchical Segmentation with Subpart Granularity in Natural Images
- SIGMA: Sinkhorn-Guided Masked Video Modeling
- Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis
- Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams
- Divide and Fuse: Body Part Mesh Recovery from Partially Visible Human Images
- Understanding Physical Dynamics with Counterfactual World Modeling
- MIGS: Multi-Identity Gaussian Splatting via Tensor Decomposition
- 4Diff: 3D-Aware Diffusion Model for Third-to-First Viewpoint Translation
- Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance
- Nymeria: A Massive Collection of Egocentric Multi-modal Human Motion in the Wild
- DreamStruct: Understanding Slides and User Interfaces via Synthetic Data Generation
- SemTrack: A Large-scale Dataset for Semantic Tracking in the Wild.
- ISBN:
- 3-031-72691-X
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