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

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.

Revisit Human-Scene Interaction via Space Occupancy.- Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control.- WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model.- Grid-Attention: Enhancing Computational Efficiency of Large Vision Models without Fine-Tuning.- Mitigating Background Shift in Class-Incremental Semantic Segmentation.- Relation DETR: Exploring Explicit Position Relation Prior for Object Detection.- BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation.- Agent Attention: On the Integration of Softmax and Linear Attention.- Learning by Aligning 2D Skeleton Sequences and Multi-Modality Fusion.- Resolving Scale Ambiguity in Multi-view 3D Reconstruction using Dual-Pixel Sensors.- Object-Oriented Anchoring and Modal Alignment in Multimodal Learning.- Towards Stable 3D Object Detection.- FYI: Flip Your Images for Dataset Distillation.- On-the-fly Category Discovery for LiDAR Semantic Segmentation.- Dual-Camera Smooth Zoom on Mobile Phones.- ProtoComp: Diverse Point Cloud Completion with Controllable Prototype.- CONDA: Condensed Deep Association Learning for Co-Salient Object Detection..- Cascade Prompt Learning for Visual-Language Model Adaptation.- PolyRoom: Room-aware Transformer for Floorplan Reconstruction.- BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models.- SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution.- HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras.- Hierarchical Unsupervised Relation Distillation for Source Free Domain Adaptation.- Customized Generation Reimagined: Fidelity and Editability Harmonized.- AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors.- Improving Video Segmentation via Dynamic Anchor Queries.- Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlights.