{"url":"/dataset/casia-v1","name":"Casia V1+","full_name":null,"description_markdown":"Casia V1 is a dataset for forgery classification. Casia V1+ is a modification of the Casia V1 dataset proposed by Chen et al. that replaces authentic images that also exist in Casiav2 with images from the COREL dataset to avoid data contamination.","description_withheld":null,"homepage":"","introduced_date":"2021-04-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/image-manipulation-detection-by-multi-view","title":"Image Manipulation Detection by Multi-View Multi-Scale Supervision","first_author":"Xinru Chen","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Manipulation Detection","url":"/task/image-manipulation-detection","datasets_with_task":"/datasets/task/image-manipulation-detection"},{"name":"Image Manipulation Localization","url":"/task/image-manipulation-localization","datasets_with_task":"/datasets/task/image-manipulation-localization"}],"languages":[],"variants":["Casia V1+"],"data_loaders":[],"num_papers_in_archive":11,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-manipulation-localization-on-casia-v1","task":"Image Manipulation Localization","dataset_variant":"Casia V1+","rows":11,"metrics":["Average Pixel F1(Fixed threshold)"],"first_row_in_archive_order":{"model":"CMX (RGB+SRM)","paper":"/paper/cmx-cross-modal-fusion-for-rgb-x-semantic","metrics":{"Average Pixel F1(Fixed threshold)":".791"},"code_links":[{"title":"huaaaliu/rgbx_semantic_segmentation","url":"https://github.com/huaaaliu/rgbx_semantic_segmentation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/image-manipulation-detection-on-casia-v1","task":"Image Manipulation Detection","dataset_variant":"Casia V1+","rows":9,"metrics":["Balanced Accuracy","AUC"],"first_row_in_archive_order":{"model":"Late Fusion","paper":"/paper/exploring-multi-modal-fusion-for-image","metrics":{"AUC":".930","Balanced Accuracy":".860"},"code_links":[{"title":"idt-iti/mmfusion-iml","url":"https://github.com/idt-iti/mmfusion-iml"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/df-net-the-digital-forensics-network-for-1","title":"DF-Net: The Digital Forensics Network for Image Forgery Detection","date":"2025-03-28","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/exploring-multi-modal-fusion-for-image","title":"MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization","date":"2023-12-04","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/trufor-leveraging-all-round-clues-for","title":"TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization","date":"2022-12-21","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/cmx-cross-modal-fusion-for-rgb-x-semantic","title":"CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers","date":"2022-03-09","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-jpeg-compression-artifacts-for-image","title":"Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization","date":"2021-08-30","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/image-manipulation-detection-by-multi-view","title":"Image Manipulation Detection by Multi-View Multi-Scale Supervision","date":"2021-04-14","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":9,"samples_unverified":4,"pointer_only_for_licence":13,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/span-spatial-pyramid-attention-network-for","title":"SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization","date":"2020-08-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/constrained-r-cnn-a-general-image","title":"Constrained R-CNN: A general image manipulation detection model","date":"2019-11-19","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/mantra-net-manipulation-tracing-network-for","title":"ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features","date":"2019-06-01","rows_on_this_dataset":2,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":15,"samples_ran":11,"samples_unverified":4,"pointer_only_for_licence":13,"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."}