Computer Vision - ECCV 2024 : 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part LI (Lecture Notes in Computer Science) (2024)

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Computer Vision - ECCV 2024 : 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part LI (Lecture Notes in Computer Science) (2024)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 493 p.
  • 商品コード 9783031729829

Full Description

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 Models as Optimizers for Efficient Planning in Offline RL.- Enhanced Sparsification via Stimulative Training.- How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs.- NeuroPictor: Refining fMRI-to-Image Reconstruction via  Multi-individual Pretraining and Multi-level Modulation.- Coarse-to-Fine Implicit Representation Learning for 3D Hand-Object Reconstruction from a Single RGB-D Image.- Efficient Snapshot Spectral Imaging: Calibration-Free Parallel Structure with Aperture Diffraction Fusion.- Enhancing Recipe Retrieval with Foundation Models: A Data Augmentation Perspective.- PapMOT: Exploring Adversarial Patch Attack against Multiple Object Tracking.- HiDiffusion:  Unlocking Higher-Resolution Creativity and Efficiency in Pretrained Diffusion Models.- On the Approximation Risk of Few-Shot Class-Incremental Learning.- Syn-to-Real Domain Adaptation for Point Cloud Completion via Part-based Approach.- Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalization.- SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning.- Region-aware Distribution Contrast: A Novel Approach to Multi-Task Partially Supervised Learning.- MasterWeaver: Taming Editability and Face Identity for Personalized Text-to-Image Generation.- PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training.- General Geometry-aware Weakly Supervised 3D Object Detection.- Long-CLIP: Unlocking the Long-Text Capability of CLIP.- Dolfin: Diffusion Layout Transformers without Autoencoder.- Real-time 3D-aware Portrait Editing from a Single Image.- StructLDM: Structured Latent Diffusion for 3D Human Generation.- Image Compression for Machine and Human Vision With Spatial-Frequency Adaptation.- Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models.- Norma: A Noise Robust Memory-Augmented Framework for Whole Slide Image Classification.- Continuous Memory Representation for Anomaly Detection.- InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser.- PACE: Pose Annotations in Cluttered Environments.

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