> ML_LITERATURE // HE-2017-MASK-R-CNN_v1.0
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, Ross Girshick · IEEE International Conference on Computer Vision (ICCV) (2017)
seminal-architecture2017industry-standardthirdPartyReproduced
Principal Contribution
Extended Faster R-CNN by adding a parallel branch for predicting pixel-level segmentation masks and introduced RoIAlign to eliminate quantization misalignment.
Operational Relevance
Serves as qualified reference for implementing task-image-segmentation, task-object-detection in production systems.
Assumptions
- Underlying spatio-temporal continuity and domain distributional stability hold
Limitations
- Performance scaling and computational footprint depend on receptive field depth, sequence length, and resolution
Connected Algorithms, Architectures & Tools
Related Algorithms:
Related Architectures:
Implementing Libraries: