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  • Produktbild: Computer Vision – ECCV 2024
  • Produktbild: Computer Vision – ECCV 2024
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Computer Vision – ECCV 2024 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXV

Aus der Reihe Lecture Notes in Computer Science
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Beschreibung

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...

Beschreibung

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.

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

26.10.2024
Abbildungen

LXXXV, 487 p. 425 illus., 186 illus. in color.
Herausgeber Aleš Leonardis + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

26.10.2024
Abbildungen

LXXXV, 487 p. 425 illus., 186 illus. in color.
Herausgeber
Verlag Springer
Seitenzahl

487
Maße (L/B/H)

23,5/15,5/3,1 cm
Gewicht

861 g
Sprache

Englisch
ISBN

978-3-031-72697-2
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Computer Vision – ECCV 2024
  • Produktbild: Computer Vision – ECCV 2024

  • VideoMamba: Spatio-Temporal Selective State Space Model.- Text to Layer-wise 3D Clothed Human Generation.- Texture-GS: Disentangle the Geometry and Texture for 3D Gaussian Splatting Editing.- Fully Sparse 3D Occupancy Prediction.- Is user feedback always informative? Retrieval Latent Defending for Semi-Supervised Domain Adaptation without Source Data.- CG-SLAM: Efficient Dense RGB-D SLAM in a Consistent Uncertainty-aware 3D Gaussian Field.- Shifted Autoencoders for Point Annotation Restoration in Object Counting.- PointLLM: Empowering Large Language Models to Understand Point Clouds.- GarmentAligner: Text-to-Garment Generation via Retrieval-augmented Multi-level Corrections.- Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving.- Enhancing Diffusion Models with Text-Encoder Reinforcement Learning.- Asymmetric Mask Scheme for Self-Supervised Real Image Denoising.- Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose Estimation.- BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting.- Forest2Seq: Revitalizing Order Prior for Sequential Indoor Scene Synthesis.- BaSIC: BayesNet Structure Learning for Computational Scalable Neural Image Compression.- FlexAttention for Efficient High-Resolution Vision-Language Models.- Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable Repainting.- AnimatableDreamer: Text-Guided Non-rigid 3D Model Generation and Reconstruction with Canonical Score Distillation.- Spatially-Variant Degradation Model for Dataset-free Super-resolution.- DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation.- Learning Exhaustive Correlation for Spectral Super-Resolution: Where Spatial-Spectral Attention Meets Linear Dependence.- Local Action-Guided Motion Diffusion Model for Text-to-Motion Generation.- EAFormer: Scene Text Segmentation with Edge-Aware Transformers.- Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects.- DetailSemNet: Elevating Signature Verification through Detail-Semantic Integration.- LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimation.