Krahasoni metodat

	Segmentim i dobët i instancave	Segmentim i instancave
Fusha	Mësimi i thellë	Mësimi i thellë
Familja	Machine learning	Machine learning
Viti i origjinës	2015–2019	2017
Krijuesi	Multiple contributors (e.g., Hsu et al., Khoreva et al.)	He, K., Gkioxari, G., Dollar, P., Girshick, R.
Lloji	Weakly supervised deep learning for pixel-wise instance delineation	Pixel-level detection and mask prediction
Burimi themelues	Hsu, C.-C., Hsu, K.-J., Tsai, C.-C., Lin, Y.-Y., & Chuang, Y.-Y. (2019). Weakly supervised instance segmentation using the bounding box tightness prior. Advances in Neural Information Processing Systems (NeurIPS), 32.	He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2961–2969.
Emërtime të tjera	WSIS, weakly-supervised mask prediction, weak-label instance segmentation, box-supervised instance segmentation	instance-level segmentation, object instance segmentation, mask prediction, panoptic instance segmentation
Të lidhura	6	4
Përmbledhja	Weakly supervised instance segmentation trains deep networks to delineate individual object instances at pixel level using only cheap, incomplete annotations — such as bounding boxes, image-level labels, or point clicks — rather than costly full pixel-wise masks. It dramatically reduces annotation effort while still producing instance-level masks for each object in an image.	Instance segmentation is a computer vision task that simultaneously detects every distinct object in an image and produces a precise pixel-level mask for each individual object instance. Unlike semantic segmentation, which labels every pixel with a class, instance segmentation distinguishes between separate objects of the same class, enabling fine-grained spatial understanding.