Weakly-supervised instance segmentation
19 papers with code • 3 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Weakly-supervised instance segmentation
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MS COCO
Latest papers with no code
Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances
Recent approaches for weakly supervised instance segmentations depend on two components: (i) a pseudo label generation model that provides instances which are consistent with a given annotation; and (ii) an instance segmentation model, which is trained in a supervised manner using the pseudo labels as ground-truth.
Weakly Supervised Instance Segmentation by Deep Community Learning
We present a weakly supervised instance segmentation algorithm based on deep community learning with multiple tasks.
Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation
Weakly-supervised instance segmentation aims to detect and segment object instances precisely, given imagelevel labels only.
Learning Instance Activation Maps for Weakly Supervised Instance Segmentation
However, learning the full extent of pixel-level instance response in a weakly supervised manner remains unexplored.
Weakly Supervised Instance Segmentation Using Hybrid Network
Weakly-supervised instance segmentation, which could greatly save labor and time cost of pixel mask annotation, has attracted increasing attention in recent years.
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation
We also combine our method with Mask R-CNN for instance segmentation, and demonstrated for the first time the ability of weakly supervised instance segmentation using only keyword annotations.
Acquire, Augment, Segment & Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products
Grocery stores have thousands of products that are usually identified using barcodes with a human in the loop.
