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Computer Vision – ECCV 2024 : 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XVI / 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 ; 15074
- 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.
- Image Processing.
- 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.
- Image Processing.
- Computer Communication Networks.
- User Interfaces and Human Computer Interaction.
- Machine Learning.
- Special Purpose and Application-Based Systems.
- Physical Description:
- 1 online resource (585 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. The papers 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:
- Diffusion Model is a Good Pose Estimator from 3D RF-Vision
- UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues
- Learning 3D-aware GANs from Unposed Images with Template Feature Field
- TAPTR: Tracking Any Point with Transformers as Detection
- Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning
- Point-supervised Panoptic Segmentation via Estimating Pseudo Labels from Learnable Distance
- BRAVE: Broadening the visual encoding of vision-language models
- HUMOS: Human Motion Model Conditioned on Body Shape
- Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields
- MVDiffHD: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction
- FlowCon: Out-of-Distribution Detection using Flow-based Contrastive Learning
- LEIA: Latent View-invariant Embeddings for Implicit 3D Articulation
- Un-EVIMO: Unsupervised Event-based Independent Motion Segmentation
- Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration
- CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
- Bayesian Evidential Deep Learning for Online Action Detection
- AdaNAT: Exploring Adaptive Policy for Token-Based Image Generation
- Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather
- Diffusion-Generated Pseudo-Observations for High-Quality Sparse-View Reconstruction
- Memory-Efficient Fine-Tuning for Quantized Diffusion Model
- VCD-Texture: Variance Alignment based 3D-2D Co-Denoising for Text-Guided Texturing
- MotionLCM: Real-time Controllable Motion Generation via Latent Consistency Model
- Human Hair Reconstruction with Strand-Aligned 3D Gaussians
- COIN: Control-Inpainting Diffusion Prior for Human and Camera Motion Estimation
- SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders
- Bridge Past and Future: Overcoming Information Asymmetry in Incremental Object Detection
- Global-to-Pixel Regression for Human Mesh Recovery.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-72640-5
- OCLC:
- 1467873922
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