paper-with-me

Dichotomous Image Segmentation 벤치마크

Dichotomous Image Segmentation on DIS-TE1

132개 결과 · ⬇ CSV · JSON

max F-Measure

0.595 0.6687 0.7425 0.8163 0.89 2015-05 2026-09 UNet — 0.625 (2015-05-18) UNet — 0.625 (2015-05-18) UNet — 0.625 (2015-05-18) UNet — 0.625 (2015-05-18) UNet — 0.625 (2015-05-18) UNet — 0.625 (2015-05-18) PSPNet — 0.645 (2016-12-04) PSPNet — 0.645 (2016-12-04) PSPNet — 0.645 (2016-12-04) PSPNet — 0.645 (2016-12-04) PSPNet — 0.645 (2016-12-04) PSPNet — 0.645 (2016-12-04) ICNet — 0.631 (2017-04-27) ICNet — 0.631 (2017-04-27) ICNet — 0.631 (2017-04-27) ICNet — 0.631 (2017-04-27) ICNet — 0.631 (2017-04-27) ICNet — 0.631 (2017-04-27) DeeplabV3+ — 0.601 (2017-06-17) DeeplabV3+ — 0.601 (2017-06-17) DeeplabV3+ — 0.601 (2017-06-17) DeeplabV3+ — 0.601 (2017-06-17) DeeplabV3+ — 0.601 (2017-06-17) DeeplabV3+ — 0.601 (2017-06-17) BSV1 — 0.595 (2018-08-02) BSV1 — 0.595 (2018-08-02) BSV1 — 0.595 (2018-08-02) BSV1 — 0.595 (2018-08-02) BSV1 — 0.595 (2018-08-02) BSV1 — 0.595 (2018-08-02) MBV3 — 0.669 (2019-05-06) MBV3 — 0.669 (2019-05-06) MBV3 — 0.669 (2019-05-06) MBV3 — 0.669 (2019-05-06) MBV3 — 0.669 (2019-05-06) MBV3 — 0.669 (2019-05-06) BASNet — 0.688 (2019-06-01) BASNet — 0.688 (2019-06-01) BASNet — 0.688 (2019-06-01) BASNet — 0.688 (2019-06-01) BASNet — 0.688 (2019-06-01) BASNet — 0.688 (2019-06-01) HRNet — 0.668 (2019-08-20) HRNet — 0.668 (2019-08-20) HRNet — 0.668 (2019-08-20) HRNet — 0.668 (2019-08-20) HRNet — 0.668 (2019-08-20) HRNet — 0.668 (2019-08-20) F3Net — 0.64 (2019-11-26) F3Net — 0.64 (2019-11-26) F3Net — 0.64 (2019-11-26) F3Net — 0.64 (2019-11-26) F3Net — 0.64 (2019-11-26) F3Net — 0.64 (2019-11-26) GCPANet — 0.598 (2020-03-02) GCPANet — 0.598 (2020-03-02) GCPANet — 0.598 (2020-03-02) GCPANet — 0.598 (2020-03-02) GCPANet — 0.598 (2020-03-02) GCPANet — 0.598 (2020-03-02) U2Net — 0.694 (2020-05-18) U2Net — 0.694 (2020-05-18) U2Net — 0.694 (2020-05-18) U2Net — 0.694 (2020-05-18) U2Net — 0.694 (2020-05-18) U2Net — 0.694 (2020-05-18) GateNet — 0.62 (2020-07-16) GateNet — 0.62 (2020-07-16) GateNet — 0.62 (2020-07-16) GateNet — 0.62 (2020-07-16) GateNet — 0.62 (2020-07-16) GateNet — 0.62 (2020-07-16) HySM — 0.695 (2020-12-21) HySM — 0.695 (2020-12-21) HySM — 0.695 (2020-12-21) HySM — 0.695 (2020-12-21) HySM — 0.695 (2020-12-21) HySM — 0.695 (2020-12-21) SINetV2 — 0.644 (2021-02-20) SINetV2 — 0.644 (2021-02-20) SINetV2 — 0.644 (2021-02-20) SINetV2 — 0.644 (2021-02-20) SINetV2 — 0.644 (2021-02-20) SINetV2 — 0.644 (2021-02-20) PFNet — 0.646 (2021-04-21) PFNet — 0.646 (2021-04-21) PFNet — 0.646 (2021-04-21) PFNet — 0.646 (2021-04-21) PFNet — 0.646 (2021-04-21) PFNet — 0.646 (2021-04-21) STDC — 0.648 (2021-04-27) STDC — 0.648 (2021-04-27) STDC — 0.648 (2021-04-27) STDC — 0.648 (2021-04-27) STDC — 0.648 (2021-04-27) STDC — 0.648 (2021-04-27) IS-Net — 0.74 (2022-03-06) IS-Net — 0.74 (2022-03-06) IS-Net — 0.74 (2022-03-06) IS-Net — 0.74 (2022-03-06) IS-Net — 0.74 (2022-03-06) IS-Net — 0.74 (2022-03-06) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) InSPyReNet (HR scale) — 0.845 (2022-09-20) InSPyReNet — 0.834 (2022-09-20) BiRefNet — 0.855 (2024-01-07) BiRefNet — 0.855 (2024-01-07) BiRefNet — 0.855 (2024-01-07) BiRefNet — 0.855 (2024-01-07) BiRefNet — 0.855 (2024-01-07) BiRefNet — 0.855 (2024-01-07) MVANet — 0.873 (2024-04-11) MVANet — 0.873 (2024-04-11) MVANet — 0.873 (2024-04-11) MVANet — 0.873 (2024-04-11) MVANet — 0.873 (2024-04-11) MVANet — 0.873 (2024-04-11) PDFNet — 0.89 (2025-03-08) PDFNet — 0.89 (2025-03-08) PDFNet — 0.89 (2025-03-08) PDFNet — 0.89 (2025-03-08) PDFNet — 0.89 (2025-03-08) PDFNet — 0.89 (2025-03-08) UNet — 0.625 (2015-05-18) PSPNet — 0.645 (2016-12-04) MBV3 — 0.669 (2019-05-06) BASNet — 0.688 (2019-06-01) U2Net — 0.694 (2020-05-18) HySM — 0.695 (2020-12-21) IS-Net — 0.74 (2022-03-06) InSPyReNet (HR scale) — 0.845 (2022-09-20) BiRefNet — 0.855 (2024-01-07) MVANet — 0.873 (2024-04-11) PDFNet — 0.89 (2025-03-08)
RankModel max F-Measureweighted F-measureMAES-MeasureE-measureHCE PaperCodeYear
21 GCPANet 0.5980.4950.1030.7050.750271 Global Context-Aware Progressive Aggregation Network for Salient Object Detection JosephChenHub/GCPANet · anish9/GCPAnet-tensorflow2.2 2020
22 BSV1 0.5950.4740.1080.6950.741288 BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation PaddlePaddle/PaddleSeg · osmr/imgclsmob · CoinCheung/BiSeNet · +18 2018
23 PDFNet 0.8900.8460.0310.8990.927 Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior tennine2077/pdfnet 2025
24 MVANet 0.8730.8230.0370.8790.911104 Multi-view Aggregation Network for Dichotomous Image Segmentation qianyu-dlut/mvanet 2024
25 BiRefNet 0.8550.8140.0380.8820.908106 Bilateral Reference for High-Resolution Dichotomous Image Segmentation zhengpeng7/birefnet 2024
26 InSPyReNet (HR scale) 0.8450.7880.0450.8730.894110 Revisiting Image Pyramid Structure for High Resolution Salient Object Detection plemeri/transparent-background · plemeri/inspyrenet · john-mnz/ComfyUI-Inspyrenet-Rembg 2022
27 InSPyReNet 0.8340.862148 Revisiting Image Pyramid Structure for High Resolution Salient Object Detection plemeri/transparent-background · plemeri/inspyrenet · john-mnz/ComfyUI-Inspyrenet-Rembg 2022
28 IS-Net 0.7400.6620.0740.7870.820149 Highly Accurate Dichotomous Image Segmentation xuebinqin/DIS 2022
29 HySM 0.6950.5970.0820.7610.803205 HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation YuvalNirkin/hyperseg 2020
30 U2Net 0.6940.6010.0830.7600.801224 U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection xuebinqin/U-2-Net · NathanUA/U-2-Net · PaddlePaddle/PaddleSeg · +26 2020
31 BASNet 0.6880.5950.0840.7540.801220 BASNet: Boundary-Aware Salient Object Detection NathanUA/BASNet · chouxianyu/Boundary-Aware-PoolNet · hamidriasat/BASNet 2019
32 MBV3 0.6690.5950.0830.7400.818274 Searching for MobileNetV3 tensorflow/models · tensorflow/models · PaddlePaddle/PaddleOCR · +64 2019
33 HRNet 0.6680.5790.0880.7420.797262 Deep High-Resolution Representation Learning for Visual Recognition open-mmlab/mmdetection · PaddlePaddle/PaddleDetection · open-mmlab/mmsegmentation · +39 2019
34 STDC 0.6480.5620.0900.7230.798249 Rethinking BiSeNet For Real-time Semantic Segmentation PaddlePaddle/PaddleSeg · Deci-AI/super-gradients · MichaelFan01/STDC-Seg · +3 2021
35 PFNet 0.6460.5520.0940.7220.786253 Camouflaged Object Segmentation with Distraction Mining Mhaiyang/CVPR2021_PFNet 2021
36 PSPNet 0.6450.5570.0890.7250.791267 Pyramid Scene Parsing Network tensorflow/models · tensorflow/models · open-mmlab/mmsegmentation · +64 2016
37 SINetV2 0.6440.5580.0940.7270.791274 Concealed Object Detection GewelsJI/SINet-V2 2021
38 F3Net 0.6400.5490.0950.7210.783244 F3Net: Fusion, Feedback and Focus for Salient Object Detection weijun88/F3Net · PanoAsh/ASOD60K · PanoAsh/SHD360 · +1 2019
39 ICNet 0.6310.5350.0950.7160.784234 ICNet for Real-Time Semantic Segmentation on High-Resolution Images osmr/imgclsmob · hszhao/ICNet · hellochick/ICNet-tensorflow · +15 2017
40 UNet 0.6250.5140.1060.7160.750233 U-Net: Convolutional Networks for Biomedical Image Segmentation labmlai/annotated_deep_learning_paper_implementations · milesial/Pytorch-UNet · open-mmlab/mmsegmentation · +484 2015
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