{"url":"/dataset/nju2k","name":"NJU2K","full_name":null,"description_markdown":"**NJU2K** is a large RGB-D dataset containing 1,985 image pairs. The stereo images were collected from the Internet and 3D movies, while photographs were taken by a Fuji W3 camera.\r\n\r\nSource: [Bifurcated Backbone Strategy for RGB-D Salient Object Detection](https://arxiv.org/abs/2007.02713)\r\nImage Source: [Depth saliency based on anisotropic center-surround difference](https://doi.org/10.1109/ICIP.2014.7025222)","description_withheld":null,"homepage":"https://drive.google.com/open?id=1R1O2dWr6HqpTOiDn6hZxUWTesOSJteQo","introduced_date":"2014-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Depth saliency based on anisotropic center-surround difference","first_author":null,"url":"https://doi.org/10.1109/ICIP.2014.7025222"},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"RGB-D Salient Object Detection","url":"/task/rgb-d-salient-object-detection","datasets_with_task":"/datasets/task/rgb-d-salient-object-detection"}],"languages":[],"variants":["NJU2K"],"data_loaders":[],"num_papers_in_archive":52,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/rgb-d-salient-object-detection-on-nju2k","task":"RGB-D Salient Object Detection","dataset_variant":"NJU2K","rows":27,"metrics":["S-Measure","Average MAE","max E-Measure","max F-Measure"],"first_row_in_archive_order":{"model":"DFormer-L","paper":"/paper/dformer-rethinking-rgbd-representation","metrics":{"Average MAE":"0.023","S-Measure":"93.7","max E-Measure":"96.4","max F-Measure":"94.6"},"code_links":[{"title":"VCIP-RGBD/DFormer","url":"https://github.com/VCIP-RGBD/DFormer"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cola-conditional-dropout-and-language-driven","title":"CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object Detection","date":"2024-07-09","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":8,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dformer-rethinking-rgbd-representation","title":"DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation","date":"2023-09-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/spsn-superpixel-prototype-sampling-network","title":"SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection","date":"2022-07-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/bts-net-bi-directional-transfer-and-selection","title":"BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection","date":"2021-04-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/uncertainty-inspired-rgb-d-saliency-detection","title":"Uncertainty Inspired RGB-D Saliency Detection","date":"2020-09-07","rows_on_this_dataset":2,"code_links":4,"syntology":null},{"paper":"/paper/siamese-network-for-rgb-d-salient-object","title":"Siamese Network for RGB-D Salient Object Detection and Beyond","date":"2020-08-26","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/depth-quality-aware-salient-object-detection","title":"Depth Quality Aware Salient Object Detection","date":"2020-08-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/cascade-graph-neural-networks-for-rgb-d","title":"Cascade Graph Neural Networks for RGB-D Salient Object Detection","date":"2020-08-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/accurate-rgb-d-salient-object-detection-via","title":"Accurate RGB-D Salient Object Detection via Collaborative Learning","date":"2020-07-23","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/rgb-d-salient-object-detection-with-cross","title":"RGB-D Salient Object Detection with Cross-Modality Modulation and Selection","date":"2020-07-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-single-stream-network-for-robust-and-real","title":"A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection","date":"2020-07-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hierarchical-dynamic-filtering-network-for","title":"Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection","date":"2020-07-13","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":4,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cross-modal-weighting-network-for-rgb-d","title":"Cross-Modal Weighting Network for RGB-D Salient Object Detection","date":"2020-07-09","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/select-supplement-and-focus-for-rgb-d","title":"Select, Supplement and Focus for RGB-D Saliency Detection","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-selective-self-mutual-attention-for","title":"Learning Selective Self-Mutual Attention for RGB-D Saliency Detection","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a2dele-adaptive-and-attentive-depth-distiller","title":"A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object Detection","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/is-depth-really-necessary-for-salient-object","title":"Is Depth Really Necessary for Salient Object Detection?","date":"2020-05-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bilateral-attention-network-for-rgb-d-salient","title":"Bilateral Attention Network for RGB-D Salient Object Detection","date":"2020-04-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/jl-dcf-joint-learning-and-densely-cooperative","title":"JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection","date":"2020-04-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/uc-net-uncertainty-inspired-rgb-d-saliency","title":"UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders","date":"2020-04-13","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/depth-induced-multi-scale-recurrent-attention","title":"Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection","date":"2019-10-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/rethinking-rgb-d-salient-object-detection","title":"Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks","date":"2019-07-15","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/contrast-prior-and-fluid-pyramid-integration","title":"Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection","date":"2019-06-01","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/progressively-complementarity-aware-fusion","title":"Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection","date":"2018-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/rgbd-salient-object-detection-via-deep-fusion","title":"RGBD Salient Object Detection via Deep Fusion","date":"2016-07-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/local-background-enclosure-for-rgb-d-salient","title":"Local Background Enclosure for RGB-D Salient Object Detection","date":"2016-06-01","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":30,"samples_ran":15,"samples_unverified":15,"pointer_only_for_licence":2,"papers_with_no_sample_that_ran":2,"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."}