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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part II / 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
- Author/Creator:
- Leonardis, Aleš.
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 15060
- 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 (582 pages)
- 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; motion estimation.
- Contents:
- SimPB: A Single Model for 2D and 3D Object Detection from Multiple Cameras
- EMDM: Efficient Motion Diffusion Model for Fast, High-Quality Human Motion Generation
- Editable Image Elements for Controllable Synthesis
- Improving 2D Feature Representations by 3D-Aware Fine-Tuning
- Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection
- PCF-Lift: Panoptic Lifting by Probabilistic Contrastive Fusion
- SemGrasp: Semantic Grasp Generation via Language Aligned Discretization
- MANIKIN: Biomechanically Accurate Neural Inverse Kinematics for Human Motion Estimation
- Simple Unsupervised Knowledge Distillation With Space Similarity
- DragAPart: Learning a Part-Level Motion Prior for Articulated Objects
- Diffusion Bridges for 3D Point Cloud Denoising
- Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging
- BAM-DETR: Boundary-Aligned Moment Detection Transformer for Temporal Sentence Grounding in Videos
- MarineInst: A Foundation Model for Marine Image Analysis with Instance Visual Description
- Superpixel-informed Implicit Neural Representation for Multi-Dimensional Data
- EgoPoser: Robust Real-Time Egocentric Pose Estimation from Sparse and Intermittent Observations Everywhere
- Physics-Free Spectrally Multiplexed Photometric Stereo under Unknown Spectral Composition
- SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction
- VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models
- Alignist: CAD-Informed Orientation Distribution Estimation by Fusing Shape and Correspondences
- Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs
- Physics-Based Interaction with 3D Objects via Video Generation
- Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussians
- Deep Patch Visual SLAM
- Surface Reconstruction for 3D Gaussian Splatting via Local Structural Hints
- HeadGaS: Real-Time Animatable Head Avatars via 3D Gaussian Splatting
- LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-72627-8
- OCLC:
- 1463770162
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