| Record Type: |
Electronic resources
: Monograph/item
|
| Title/Author: |
Computer vision - ECCV 2024 Workshops/ edited by Alessio Del Bue ... [et al.]. |
| Reminder of title: |
Milan, Italy, September 29-October 4, 2024 : proceedings. |
| remainder title: |
ECCV 2024 Workshops |
| other author: |
Del Bue, Alessio. |
| corporate name: |
European Conference on Computer Vision |
| Published: |
Cham :Springer Nature Switzerland : : 2025., |
| Description: |
lvi, 398 p. :ill. (some col.), digital ;24 cm. |
| [NT 15003449]: |
MobileIQA: Exploiting Mobile-level Diverse Opinion Network For No-Reference Image Quality Assessment Using Knowledge Distillation -- AIM 2024 Sparse Neural Rendering Challenge: Methods and Results -- AIM 2024 Sparse Neural Rendering Challenge: Dataset and Benchmark -- Unsupervised Anomaly Segmentation at High Resolution with Patch-Divide-and-Conquer and Self-Ensembling -- Compression-RQ-VQA: Leveraging Rich Quality-aware Features for Compressed Video Quality Assessment -- Learning from Strong to Weak - An Enhanced Quality Comparison Network via Efficient Transfer Learning -- Assessing UHD Image Quality from Aesthetics, Distortions, and Saliency -- AVSal: Enhancing Video Saliency Prediction through Audio-Visual Fusion and Temporal Aggregation -- SR-VQA: Super-Resolution Video Quality Assessment Model -- AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results -- AIM 2024 Challenge on Video Saliency Prediction: Methods and Results -- Advancing Few-Shot Novel View Synthesis with Teacher-Student Guided Scene Geometry Refinement -- AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results -- TASOD: A Data Collection for Tiny and Small Object Detection -- Effective Prior Regularized Sparse Learning -- AIM 2024 Challenge on UHD Blind Photo Quality Assessment -- Compressed Depth Map Super-Resolution and Restoration: AIM 2024 Challenge Results -- AIM 2024 Challenge on Efficient Video Super-Resolution for AV1 Compressed Content -- Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation -- Leveraging Object Priors for Point Tracking -- PVUW 2024 Challenge on Complex Video Understanding: Methods and Results -- LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation. |
| Contained By: |
Springer Nature eBook |
| Subject: |
Computer vision - Congresses. - |
| Online resource: |
https://doi.org/10.1007/978-3-031-91856-8 |
| ISBN: |
9783031918568 |