9 citations · 9 across the 7 of their papers we have counts for
5 papers · 1 filter
MARIO: A Mixed Annotation Framework For Polyp Segmentation
Haoyang Li, Yiwen Hu, Jun Wei +1
Existing polyp segmentation models are limited by high labeling costs and the small size of datasets. Additionally, vast polyp datasets remain underutilized because these models ty…
MixPolyp: Integrating Mask, Box and Scribble Supervision for Enhanced Polyp Segmentation
Yiwen Hu, Jun Wei, Yuncheng Jiang +4
Limited by the expensive labeling, polyp segmentation models are plagued by data shortages. To tackle this, we propose the mixed supervised polyp segmentation paradigm (MixPolyp).…
Let Video Teaches You More: Video-to-Image Knowledge Distillation using DEtection TRansformer for Medical Video Lesion Detection
Yuncheng Jiang, Zixun Zhang, Jun Wei +5
AI-assisted lesion detection models play a crucial role in the early screening of cancer. However, previous image-based models ignore the inter-frame contextual information present…
BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations
Jun Wei, Yiwen Hu, Guanbin Li +3
Accurate polyp segmentation is of great importance for colorectal cancer diagnosis and treatment. However, due to the high cost of producing accurate mask annotations, existing pol…
Shallow Attention Network for Polyp Segmentation
Jun Wei, Yiwen Hu, Ruimao Zhang +3
Accurate polyp segmentation is of great importance for colorectal cancer diagnosis. However, even with a powerful deep neural network, there still exists three big challenges that…