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Found 5 papers, 4 papers with code
Stochastic Segmentation with Conditional Categorical Diffusion Models
Semantic segmentation has made significant progress in recent years thanks to deep neural networks, but the common objective of generating a single segmentation output that accurately matches the image's content may not be suitable for safety-critical domains such as medical diagnostics and autonomous driving.
Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation
We apply contrastive learning to enhance the discriminative power of the multi-scale features extracted by semantic segmentation networks.
2020 CATARACTS Semantic Segmentation Challenge
In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set.
Effective semantic segmentation in Cataract Surgery: What matters most?
Our work proposes neural network design choices that set the state-of-the-art on a challenging public benchmark on cataract surgery, CaDIS.
Ranked #1 on
2D Semantic Segmentation task 1 (8 classes)
on CaDIS
2D Semantic Segmentation task 1 (8 classes)
2D Semantic Segmentation task 2 (17 classes)
+2
Deep iterative vessel segmentation in OCT angiography
This paper addresses retinal vessel segmentation on optical coherence tomography angiography (OCT-A) images of the human retina.
