{"url":"/dataset/avsbench","name":"AVSBench","full_name":"Audio −Visual Segmentation","description_markdown":"**AVSBench** is a pixel-level audio-visual segmentation benchmark that provides ground truth labels for sounding objects. The dataset is divided into three subsets: AVSBench-object (Single-source subset, Multi-sources subset) and AVSBench-semantic (Semantic-labels subset). Accordingly, three settings are studied: \r\n\r\n1) semi-supervised audio-visual segmentation with a single sound source\r\n\r\n2) fully-supervised audio-visual segmentation with multiple sound sources\r\n\r\n3) fully-supervised audio-visual semantic segmentation\r\n\r\nSource: [Audio-Visual Segmentation with Semantics](https://arxiv.org/pdf/2301.13190v1.pdf)","description_withheld":null,"homepage":"http://www.avlbench.opennlplab.cn/download","introduced_date":"2023-01-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/audio-visual-segmentation-with-semantics","title":"Audio-Visual Segmentation with Semantics","first_author":"Jinxing Zhou","url":null},"license":{"name":"Apache-2.0 license","url":"https://github.com/OpenNLPLab/AVSBench/blob/main/LICENSE"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Video Object Segmentation","url":"/task/video-object-segmentation","datasets_with_task":"/datasets/task/video-object-segmentation"}],"languages":[],"variants":["AVSBench"],"data_loaders":[],"num_papers_in_archive":20,"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."}