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Volume segmentation of a 3D-rendered CT scan of the thorax: ... Semantic segmentation is an approach detecting, for every pixel, the belonging class. [18]
U-Net was created by Olaf Ronneberger, Philipp Fischer, Thomas Brox in 2015 and reported in the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation". [1] It is an improvement and development of FCN: Evan Shelhamer, Jonathan Long, Trevor Darrell (2014). "Fully convolutional networks for semantic segmentation". [2]
Segmentation, classification 2012 [107] [108] R. Bhatt. Bosphorus 3D Face image database. 34 action units and 6 expressions labeled; 24 facial landmarks labeled. 4652 Images, text Face recognition, classification 2008 [109] [110] A Savran et al. UOY 3D-Face neutral face, 5 expressions: anger, happiness, sadness, eyes closed, eyebrows raised ...
CloudCompare is a 3D point cloud processing software (such as those obtained with a laser scanner).It can also handle triangular meshes and calibrated images. Originally created during a collaboration between Telecom ParisTech and the R&D division of EDF, the CloudCompare project began in 2003 with the PhD of Daniel Girardeau-Montaut on Change detection on 3D geometric data. [2]
Cipolla is known for his research contributions to the reconstruction, registration and recognition of three-dimensional objects from images. These include novel algorithms for the recovery of accurate 3D shape, visual localisation and tracking, and semantic segmentation and their practical application.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Given an image (or an image-like feature map), selective search (also called Hierarchical Grouping) first segments the image by the algorithm in (Felzenszwalb and Huttenlocher, 2004), [13] then performs the following: [2]
Example video frames and their object co-segmentation annotations (ground truth) in the Noisy-ViDiSeg [1] dataset. Object segments are depicted by the red edge. In computer vision, object co-segmentation is a special case of image segmentation, which is defined as jointly segmenting semantically similar objects in multiple images or video ...