Semantic Segmentation

• Semantic Segmentation with Second Order Pooling (CVPR'12)

• Generate bottom-up multiple obj-vs-background region using binary graph-cuts
• Generate second order pooling features on each region
• extract dense SIFT (dense points inside a region)>create covariance matrix (hence second order)->take max/avg on the covariance matrix
• Learn simple linear-svm classifier to classify region
• Semantic Segmentation done by sequentially overlaying the classified regions
• Does better than Berkeley vision classification on PASCAL VOC challenge. 
• No codebook required to learn
• Emphasizes pooling operations
• Unlike first order max/average pooling, emphasizes second order pooling which results into better features (experimentally)
• Faster learning/classification due to simple classifier unlike kernel-svms

• Perceptual Organization (CVPR'13)

• Fully Convolutional Network (CVPR'15)

• Rest
  

• Top-open-source-semantic-segmentation-projects-with-some-extra-learning-resources-available-online