Abstract
This paper introduces a LArge-scale Video Interpolation Benchmark (LAVIB) for the low-level video task of Video Frame Interpolation (VFI). LAVIB comprises a large collection of high-resolution videos sourced from the web through an automated pipeline with minimal requirements for human verification. Metrics are computed for each video's motion magnitudes, luminance conditions, frame sharpness, and contrast. The collection of videos and the creation of quantitative challenges based on these metrics are under-explored by current low-level video task datasets. In total, LAVIB includes 283K clips from 17K ultra-HD videos, covering 77.6 hours. Benchmark train, val, and test sets maintain similar video metric distributions. Further splits are also created for out-of-distribution (OOD) challenges, with train and test splits including videos of dissimilar attributes.
| Original language | English |
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| Title of host publication | Advances in Neural Information Processing Systems 37 (NeurIPS 2024) |
| Subtitle of host publication | Datasets and Benchmarks Track |
| Editors | A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, C. Zhang |
| Volume | 37 |
| Publication status | Published - 2024 |
| Event | 38th Annual Conference on Neural Information Processing Systems, NeurIPS 2024 - Vancouver, Canada Duration: 9 Dec 2024 → 15 Dec 2024 Conference number: 38 https://neurips.cc/Conferences/2024 |
Publication series
| Name | Advances in Neural Information Processing Systems |
|---|---|
| Publisher | Neural information processing systems foundation |
| ISSN (Print) | 1049-5258 |
Conference
| Conference | 38th Annual Conference on Neural Information Processing Systems, NeurIPS 2024 |
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| Abbreviated title | NeurIPS 2024 |
| Country/Territory | Canada |
| City | Vancouver |
| Period | 9/12/24 → 15/12/24 |
| Internet address |