TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/ACSNet

ACSNet

Reported on 12 benchmarks across 1 task

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical12 results

  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    Dice
    0.713
    best: 0.9 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    S measure
    0.782
    best: 0.9 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    Sensitivity
    0.601
    best: 83.7 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    mean E-measure
    0.779
    best: 93.8 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    mean F-measure
    0.688
    best: 93.8 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Easy (Unseen)
    weighted F-measure
    0.642
    best: 0.794 (SALI)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    Dice
    0.708
    best: 0.902 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    S-Measure
    0.783
    best: 0.894 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    Sensitivity
    0.618
    best: 0.852 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    mean E-measure
    0.787
    best: 0.941 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    mean F-measure
    0.684
    best: 0.932 (YOLO-SAM 2)
  • Medical Image SegmentationonSUN-SEG-Hard (Unseen)
    weighted F-measure
    0.636
    best: 0.79 (SALI)