Computer Vision – ECCV 2024
Springer International Publishing (Verlag)
978-3-031-72994-2 (ISBN)
- Noch nicht erschienen - erscheint am 28.12.2024
- Versandkostenfrei
- Auch auf Rechnung
- Artikel merken
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.
KFD-NeRF: Rethinking Dynamic NeRF with Kalman Filter.- Physical-Based Event Camera Simulator.- V-IRL: Grounding Virtual Intelligence in Real Life.- Adversarial Prompt Tuning for Vision-Language Models.- Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing.- Mono-ViFI: A Unified Learning Framework for Self-supervised Single- and Multi-frame Monocular Depth Estimation.- CC-SAM: Enhancing SAM with Cross-feature Attention and Context for Ultrasound Image Segmentation.- An Efficient and Effective Transformer Decoder-Based Framework for Multi-Task Visual Grounding.- Think2Drive: Efficient Reinforcement Learning by Thinking with Latent World Model for Autonomous Driving (in CARLA-v2).- PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion.- X-InstructBLIP: A Framework for Aligning Image, 3D, Audio, Video to LLMs and its Emergent Cross-modal Reasoning.- Learning Neural Volumetric Pose Features for Camera Localization.- Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation.- REFRAME: Reflective Surface Real-Time Rendering for Mobile Devices.- Self-Training Room Layout via Geometry-aware Ray-casting.- Closed-Loop Unsupervised Representation Disentanglement with $beta$-VAE Distillation and Diffusion Probabilistic Feedback.- Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective.- Every Pixel Has its Moments: Ultra-High-Resolution Unpaired Image-to-Image Translation via Dense Normalization.- ZoLA: Zero-Shot Creative Long Animation Generation with Short Video Model.- Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach.- Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-One Image Restoration.- When Fast Fourier Transform Meets Transformer for Image Restoration.- Dolphins: Multimodal Language Model for Driving.- Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model.- CamoTeacher: Dual-Rotation Consistency Learning for Semi-Supervised Camouflaged Object Detection.- Placing Objects in Context via Inpainting for Out-of-distribution Segmentation.- Textual Grounding for Open-vocabulary Visual Information Extraction in Layout-diversified Documents.
| Erscheint lt. Verlag | 28.12.2024 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | Approx. 505 p. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Mathematik / Informatik ► Informatik ► Netzwerke | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | Artificial Intelligence • Computer Networks • Computer systems • computer vision • Education • Human-Computer Interaction (HCI) • Image Analysis • image coding • Image Processing • image reconstruction • Image Segmentation • learning • machine learning • Object recognition • pattern recognition • reconstruction • Signal Processing • Software engineering |
| ISBN-10 | 3-031-72994-3 / 3031729943 |
| ISBN-13 | 978-3-031-72994-2 / 9783031729942 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
