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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LXXXVIII / 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 ; 15146
- 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 (596 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:
- HyperSpaceX: Radial and Angular Exploration of HyperSpherical Dimensions
- InstructGIE: Towards Generalizable Image Editing
- HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimation
- Navigating Text-to-Image Generative Bias across Indic Languages
- Correspondence-Free SE(3) Point Cloud Registration in RKHS via Unsupervised Equivariant Learning
- CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models
- Nickel and Diming Your GAN: A Dual-Method Approach to Enhancing GAN Efficiency via Knowledge Distillation
- VividDreamer: Invariant Score Distillation for Hyper-Realistic Text-to-3D Generation
- A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation
- Towards Scene Graph Anticipation
- Non-Line-of-Sight Estimation of Fast Human Motion with Slow Scanning Imagers
- Distributed Semantic Segmentation with Efficient Joint Source and Task Decoding
- NePhi: Neural Deformation Fields for Approximately Diffeomorphic Medical Image Registration
- Aligning Neuronal Coding of Dynamic Visual Scenes with Foundation Vision Models
- Image Manipulation Detection With Implicit Neural Representation and Limited Supervision
- Scalar Function Topology Divergence: Comparing Topology of 3D Objects
- Introducing Routing Functions to Vision-Language Parameter-Efficient Fine-Tuning with Low-Rank Bottlenecks
- Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models
- DeTra: A Unified Model for Object Detection and Trajectory Forecasting
- ControlNet-XS: Rethinking the Control of Text-to-Image Diffusion Models as Feedback-Control Systems
- Adaptive Bounding Box Uncertainties via Two-Step Conformal Prediction
- Common Sense Reasoning for Deep Fake Detection
- Let the Avatar Talk using Texts without Paired Training Data
- NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields
- GOEmbed: Gradient Origin Embeddings for Representation Agnostic 3D Feature Learning
- Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks
- AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 9783031732232
- 3031732235
- OCLC:
- 1465266532
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