Error-Tolerant Scribbles Based Interactive Image Segmentation
By Junjie Bai, Xiaodong Wu. 2014
81 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Ming-Ming Cheng
- Ilya A. Petrov
- Konstantin Sofiiuk
- Anton Konushin
- Zheng Lin
- Zhiyan Zhao
- Yilei Zhang
- Xi Chen
In Human-Computer Interaction
- Konstantin Sofiiuk
- Ilya A. Petrov
- Anton Konushin
- Zhiyan Zhao
- Yilei Zhang
- Zheng Lin
- Xi Chen
- Zhao Zhang
Citations in the corpus
- FocalClick: Towards Practical Interactive Image Segmentation (2022, background): “It enables users to annotate masks conveniently using simple interactions like scribbles [1, 11, 21], boxes [20, 34, 40], or clicks [5, 18, 27, 35, 36, 44].”
- Reviving Iterative Training with Mask Guidance for Interactive Segmentation (2021, methodology): “Scribbles are used in many early works [5, 15, 16, 17, 26].”
- Interactive Image Segmentation With First Click Attention (2020, methodology): “[2] provided an error-tolerant method, which allows users to have some wrong interactions.”
- F-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation (2020, background): “Interactive segmentation has been a topic of research for a long time [26, 10, 11, 13, 2, 31, 18, 22, 15].”
- EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow (2021, background): “In general, interactive information could be various inputs, such as scribbles [4], clicks [47, 29, 46], bounding boxes [50] and so on.”
- FocusCut: Diving into a Focus View in Interactive Segmentation (2022, background): “For the former, the interactive modes are widely explored and mainly based on the bounding box [50], the polygon [1, 6, 32], clicks [2, 29, 36], scribbles [3, 48], and some combinations [34, 52].”
- Conditional Diffusion for Interactive Segmentation (2021, methodology): “GrabCut Berkeley SBD DAVIS Method NoC@85 NoC@90 NoC@90 NoC@85 NoC@90 NoC@85 NoC@90 Graph cut [2] 7.”
- Interactive Image Segmentation via Backpropagating Refinement Scheme (2019, methodology): “To alleviate user efforts, [47, 1] develop error-tolerant interactive image segmentation algorithms.”