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Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
Ranked #1 on Real-Time Object Detection on COCO minival (MAP metric)
3D INSTANCE SEGMENTATION HUMAN PART SEGMENTATION KEYPOINT DETECTION MULTI-HUMAN PARSING MULTI-PERSON POSE ESTIMATION MULTI-TISSUE NUCLEUS SEGMENTATION NUCLEAR SEGMENTATION PANOPTIC SEGMENTATION REAL-TIME OBJECT DETECTION
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
We consider image transformation problems, where an input image is transformed into an output image.
Ranked #5 on Nuclear Segmentation on Cell17
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow.
Ranked #1 on Multi-tissue Nucleus Segmentation on Kumar
Histology images are inherently symmetric under rotation, where each orientation is equally as likely to appear.
Ranked #1 on Breast Tumour Classification on PCam