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Found 2 papers, 1 papers with code
Incorporating Depth into both CNN and CRF for Indoor Semantic Segmentation
To improve segmentation performance, a novel neural network architecture (termed DFCN-DCRF) is proposed, which combines an RGB-D fully convolutional neural network (DFCN) with a depth-sensitive fully-connected conditional random field (DCRF).
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
Indoor semantic segmentation has always been a difficult task in computer vision.
Ranked #26 on
Semantic Segmentation
on SUN-RGBD
(using extra training data)
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