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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LXXXIII / 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

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Format:
Book
Author/Creator:
Leonardis, Aleš.
Contributor:
Ricci, Elisa.
Roth, Ștefan.
Russakovsky, Olga.
Sattler, Torsten.
Varol, Gül.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 15141
Language:
English
Subjects (All):
Image processing--Digital techniques.
Image processing.
Computer vision.
Computer networks.
User interfaces (Computer systems).
Human-computer interaction.
Machine learning.
Computers, Special purpose.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer Communication Networks.
User Interfaces and Human Computer Interaction.
Machine Learning.
Special Purpose and Application-Based Systems.
Local Subjects:
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer Communication Networks.
User Interfaces and Human Computer Interaction.
Machine Learning.
Special Purpose and Application-Based Systems.
Physical Description:
1 online resource (565 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:
LG-Gaze: Learning Geometry-aware Continuous Prompts for Language-Guided Gaze Estimation
Efficient Training with Denoised Neural Weights
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning
Integration of Global and Local Representations for Fine-grained Cross-modal Alignment
Local and Global Flatness for Federated Domain Generalization
SRPose: Two-view Relative Pose Estimation with Sparse Keypoints
Deep Reward Supervisions for Tuning Text-to-Image Diffusion Models
Paying More Attention to Images: A Training-Free Method for Alleviating Hallucination in LVLMs
Inf-DiT: Upsampling any-resolution image with memory-efficient diffusion transformer.
Implicit Neural Models to Extract Heart Rate from Video
Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering
PFGS: High Fidelity Point Cloud Rendering via Feature Splatting
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
E3M: Zero-Shot Spatio-Temporal Video Grounding with Expectation-Maximization Multimodal Modulation
EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions
LMT-GP: Combined Latent Mean-Teacher and Gaussian Process for Semi-supervised Low-light Image Enhancement
Veil Privacy on Visual Data: Concealing Privacy for Humans, Unveiling for DNNs
Efficient Vision Transformers with Partial Attention
Generalized Coverage for More Robust Low-Budget Active Learning
Rasterized Edge Gradients: Handling Discontinuities Differentially
Enhancing Cross-Subject fMRI-to-Video Decoding with Global-Local Functional Alignment
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning
LLaVA-UHD: an LMM Perceiving any Aspect Ratio and High-Resolution Images
Learning Natural Consistency Representation for Face Forgery Video Detection
ZeroI2V: Zero-Cost Adaptation of Pre-Trained Transformers from Image to Video
Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems
R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
9783031730108
3031730100
OCLC:
1465266532

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