5 research outputs found
Bidirectional Graph Reasoning Network for Panoptic Segmentation
Recent researches on panoptic segmentation resort to a single end-to-end
network to combine the tasks of instance segmentation and semantic
segmentation. However, prior models only unified the two related tasks at the
architectural level via a multi-branch scheme or revealed the underlying
correlation between them by unidirectional feature fusion, which disregards the
explicit semantic and co-occurrence relations among objects and background.
Inspired by the fact that context information is critical to recognize and
localize the objects, and inclusive object details are significant to parse the
background scene, we thus investigate on explicitly modeling the correlations
between object and background to achieve a holistic understanding of an image
in the panoptic segmentation task. We introduce a Bidirectional Graph Reasoning
Network (BGRNet), which incorporates graph structure into the conventional
panoptic segmentation network to mine the intra-modular and intermodular
relations within and between foreground things and background stuff classes. In
particular, BGRNet first constructs image-specific graphs in both instance and
semantic segmentation branches that enable flexible reasoning at the proposal
level and class level, respectively. To establish the correlations between
separate branches and fully leverage the complementary relations between things
and stuff, we propose a Bidirectional Graph Connection Module to diffuse
information across branches in a learnable fashion. Experimental results
demonstrate the superiority of our BGRNet that achieves the new
state-of-the-art performance on challenging COCO and ADE20K panoptic
segmentation benchmarks.Comment: CVPR202
Lack of an association of miR-938 SNP in IDDM10 with human type 1 diabetes
MicroRNAs (miRNAs) are a newly discovered type of small non-protein coding RNA that function in the inhibition of effective mRNA translation, and may serve as susceptibility genes for various disease developments. The SNP rs12416605, located in human type 1 diabetes IDDM10 locus, changes the seeding sequence (UGU[G/A]CCC) of miRNA miR-938 and potentially alters miR-938 targets, including IL-16 and IL-17A. In an attempt to test whether miR-938 may be a susceptibility gene for IDDM10, we assessed the possible association of the miR-938 SNP with T1D in an American Caucasian cohort of 622 patients and 723 healthy controls by TaqMan assay. Our current data do not support the association between the SNP in miR-938 and type 1 diabetes