Buch, Englisch, 387 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 668 g
Milan, Italy, September 29-October 4, 2024, Proceedings, Part VII
Buch, Englisch, 387 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 668 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-031-91766-0
Verlag: Springer Nature Switzerland
The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29–October 4, 2024.
These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of workshops and distribution of the workshop papers in the LNCS volumes can be found in the preface that is freely accessible online.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
Weitere Infos & Material
Valeo4Cast: A Modular Approach to End-to-End Forecasting.- AA-SGAN: Adversarially Augmented Social GAN with Synthetic Data.- Autonomous Drone-Person Tracking and Following in Uniform Appearance Scenarios.- Continual Reinforcement Learning with Implicit Generative Replay for Autonomous Driving.- Self-supervised Road Accident Anticipation with Non-decreasing Danger.- 3D Object Detection and Tracking Refinement with Ensemble Methods and Spatiotemporal Filtering.- Conditional Unscented Autoencoders for Trajectory Prediction.- Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation.- TrackLidFormer: a Transformer-based Approach for Occluded Object Tracking.- Good Data Is All Imitation Learning Needs.- What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon.- High Dynamic Range Modulo Imaging for Robust Object Detection in Autonomous Driving.- RLNet: Adaptive Fusion of 4D Radar and Lidar for 3D Object Detection.- Improving Online Source-Free Domain Adaptation for Object Detection by Unsupervised Data Acquisition.- AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving.- On Camera and LiDAR Positions in End-to-End Autonomous Driving.- ProGBA: Prompt Guided Bayesian Augmentation for Zero-shot Domain Adaptation.- ReGentS: Real-World Safety-Critical Driving Scenario Generation Made Stable.- Loop Mining Large-Scale Unlabeled Data for Corner Case Detection in Autonomous Driving.- HumanSim: Human-Like Multi-Agent Novel Driving Simulation for Corner Case Generation.- Talk to Parallel LiDARs: A Human-LiDAR Interaction Method Based on 3D Visual Grounding.- RoSA Dataset: Road Construct zone Segmentation for Autonomous Driving.- A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection.- The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results.
