Research map / Detection and segmentation / CNN features
Gaussian Conditional Random Field Network for Semantic Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add the GCRF network to the DeepLab CNN unary network | DeepLab CNN · PASCALVOC 2012 test | mean IoU: 6.2 points | Helped |
| Use the proposed GCRF network instead of Deep message passing | Semantic segmentation · PASCALVOC 2012 test | mean IoU: lower by just 0.2 points | Hurt |
Closest papers by meaning
- Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising (CVPR 2016 · similarity 0.89)
- Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond (NeurIPS 2021 · similarity 0.89)
- Efficient Linear Programming for Dense CRFs (CVPR 2017 · similarity 0.88)
- E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation (ICLR 2023 · similarity 0.88)
- Deep Spatio-Temporal Random Fields for Efficient Video Segmentation (CVPR 2018 · similarity 0.86)
- Unleashing the Power of Visual Foundation Models for Generalizable Semantic Segmentation (AAAI 2025 · similarity 0.83)
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