Computer Vision ECCV 2024: 18th European Conference, Milan, Italy, September 2 [Paperback]

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 29October 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.

GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation.- IRGen: Generative Modeling for Image Retrieval.- Learning Trimodal Relation for Audio-Visual Question Answering with Missing Modality.- FastCAD: Real-Time CAD Retrieval and Alignment from Scans and Videos.- A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting.- VISA: Reasoning Video Object Segmentation via Large Language Model.- Lego: Learning to Disentangle and Invert Personalized Concepts Beyond Object Appearance in Text-to-Image Diffusion Models.- IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth Generation.- Scaling Backwards: Minimal Synthetic Pre-training?.- BAMM: Bidirectional Autoregressive Motion Model.- Event-based Head Pose Estimation: Benchmark and Method.- Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head Videos.- Towards Multi-modal Transformers in Federated Learning.- Fisher Calibration for Backdoor-Robust Heterogeneous Federated Learning.- QueryCDR: Query-based Controllable Distortion Rectification Network for Fisheye Images.- Latent-INR: A Flexible Framework for Implicit Representations of Videos with Discriminative Semantics.- DCDM: Dlĥ