{"url":"/dataset/iisc-veed","name":"IISc VEED","full_name":"Indian Institute of Science Virtual Environment Exploration Database of Static Scenes","description_markdown":"**IISc VEED** consists of 200 diverse indoor and outdoor scenes (see samples below). The videos are rendered with blender and the blend files are obtained for the scenes mainly from blendswap and turbosquid. 4 different camera trajectories are added to each scene and thus we have a total of 800 videos. The videos are rendered at full HD resolution (1920 x 1080) and at 30fps and contain 12 frames each.\r\n\r\nSource: [Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction](https://nagabhushansn95.github.io/publications/2021/ivp.html#database)\r\n\r\nImage Source: [https://nagabhushansn95.github.io/publications/2021/ivp.html#database](https://nagabhushansn95.github.io/publications/2021/ivp.html#database)","description_withheld":null,"homepage":"https://nagabhushansn95.github.io/publications/2021/ivp.html#database","introduced_date":"2021-10-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/revealing-disocclusions-in-temporal-view","title":"Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction","first_author":"Vijayalakshmi Kanchana","url":null},"license":null,"modalities":[],"tasks":[{"name":"Temporal View Synthesis","url":"/task/temporal-view-synthesis","datasets_with_task":"/datasets/task/temporal-view-synthesis"}],"languages":[],"variants":["IISc VEED"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}