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Budget-aware Semi-Supervised
Semantic and Instance Segmentation
Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Women In Computer Vision - CVPR 2019
Motivation
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semantic segmentation Instance segmentation
Pixel-level
annotations are
expensive!
Motivation
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semantic segmentation Instance segmentation
Solution: Weakly and
Semi-supervised methods!
Motivation
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semantic segmentation Instance segmentation
Solution: Weakly and
Semi-supervised methods!
Contributions
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
1. We unify the segmentation benchmarks regardless the training setting and the supervision signals
comparing them in terms of the total annotation cost.
Contributions
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
1. We unify the segmentation benchmarks regardless the training setting and the supervision signals
comparing them in terms of the total annotation cost.
2. We experiment with a semi-supervised pipeline and test it in Pascal VOC for semantic and instance
segmentation, outperforming previous works at low annotated budgets.
Contributions
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
1. We unify the segmentation benchmarks regardless the training setting and the supervision signals
comparing them in terms of the total annotation cost.
2. We experiment with a semi-supervised pipeline and test it in Pascal VOC for semantic and instance
segmentation, outperforming previous works at low annotated budgets.
3. We show that for low annotation budgets, it’s more convenient having fewer but stronger-labeled data
over having larger weakly-annotated sets.
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semi-Supervised PipelineSemi-Supervised Pipeline
Annotation
network
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semi-Supervised PipelineSemi-Supervised Pipeline
Annotation
network
Segmentation
network
Experimental validation for Pascal VOC
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semantic segmentation
Annotation cost
Segmentationquality
We used DeepLab v3+ for both the
annotation and segmentation network
Experimental validation for Pascal VOC
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Instance segmentation
Annotation cost
Segmentationquality
We used RSIS for both the annotation
and segmentation network
Comparison to other works
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Semantic segmentation Instance segmentation
Annotation cost
Segmentationquality
Visualization for semantic segmentation
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Visualization for instance segmentation
Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
Thanks for
your attention!

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Budget-aware Semi-Supervised Semantic and Instance Segmentation

  • 1. Budget-aware Semi-Supervised Semantic and Instance Segmentation Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Women In Computer Vision - CVPR 2019
  • 2. Motivation Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semantic segmentation Instance segmentation Pixel-level annotations are expensive!
  • 3. Motivation Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semantic segmentation Instance segmentation Solution: Weakly and Semi-supervised methods!
  • 4. Motivation Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semantic segmentation Instance segmentation Solution: Weakly and Semi-supervised methods!
  • 5. Contributions Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto 1. We unify the segmentation benchmarks regardless the training setting and the supervision signals comparing them in terms of the total annotation cost.
  • 6. Contributions Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto 1. We unify the segmentation benchmarks regardless the training setting and the supervision signals comparing them in terms of the total annotation cost. 2. We experiment with a semi-supervised pipeline and test it in Pascal VOC for semantic and instance segmentation, outperforming previous works at low annotated budgets.
  • 7. Contributions Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto 1. We unify the segmentation benchmarks regardless the training setting and the supervision signals comparing them in terms of the total annotation cost. 2. We experiment with a semi-supervised pipeline and test it in Pascal VOC for semantic and instance segmentation, outperforming previous works at low annotated budgets. 3. We show that for low annotation budgets, it’s more convenient having fewer but stronger-labeled data over having larger weakly-annotated sets.
  • 8. Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semi-Supervised PipelineSemi-Supervised Pipeline Annotation network
  • 9. Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semi-Supervised PipelineSemi-Supervised Pipeline Annotation network Segmentation network
  • 10. Experimental validation for Pascal VOC Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semantic segmentation Annotation cost Segmentationquality We used DeepLab v3+ for both the annotation and segmentation network
  • 11. Experimental validation for Pascal VOC Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Instance segmentation Annotation cost Segmentationquality We used RSIS for both the annotation and segmentation network
  • 12. Comparison to other works Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto Semantic segmentation Instance segmentation Annotation cost Segmentationquality
  • 13. Visualization for semantic segmentation Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto
  • 14. Visualization for instance segmentation Budget-aware Semi-Supervised Semantic and Instance Segmentation: Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto