• May 07, 2020 · Introduction. Stroke remains a common affliction and is associated with significant morbidity and mortality. It is a leading cause of serious long-term disability; the direct and indirect costs of stroke were $45.5 billion between 2014 to 2015 in the United States.1 Large vessel occlusion (LVO) accounts for nearly half of the patients with acute ischemic stroke (AIS) presenting to tertiary ...
  • segmentation datasets label a single two-dimensional region partition. Our annotation model, outlined in Figure2, captures the object-part-subpart decomposition, as well as the occlusion relationships (e.g. apple in front of jacket, glasses in front of face) present in the scene.
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Sep 05, 2016 · The relative frequency of acute intracranial large vessel occlusion (LVO) in patients with acute ischemic stroke (AIS) who could be candidate for intra-arterial treatment (IAT) is not well known. In this study, we determined clinical variables associated with LVO and the proportion of patients with LVO among patients presenting with AIS within 6 h of symptom onset. Data of consecutive patients ...
3. PREVIOUS WORK IN FACE RECOGNITION WITH OCCLUSION. Color-based segmentation [1] Explicit occlusion detection with block-level classifiers [2] [1] Rui Min, Abdenour Hadid, and Jean-Luc Dugelay. Improving the recognition of faces occluded by facial accessories. In Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011
Oct 22, 2018 · 3. HoG Face Detector in Dlib. This is a widely used face detection model, based on HoG features and SVM. You can read more about HoG in our post.The model is built out of 5 HOG filters – front looking, left looking, right looking, front looking but rotated left, and a front looking but rotated right.
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    UTKFace dataset is a large-scale face dataset with long age span, which ranges from 0 to 116 years old. The images cover large variation in pose, facial expression, illumination, occlusion, resolution and other such. Size: The dataset consists of over 20K images with annotations of age, gender and ethnicity.provided even under occlusion. The dataset is composed of images from new and existing datasets such as LFPW [18], HELEN [19], AFW [20], and 300-W face datasets with landmarks provided by the 300-W challenge [21][22][23]. The provided annotations from the 300-W datasets do not attempt to annotate every face in the image, so AFLW is 105 subjects in various poses, expressions and occlusion conditions. The majority of the subjects are aged between 25 and 35. There are 60 men and 45 women in total. Most of the subjects are Caucasian. 29 professional actors/actresses are incorporated in the database. 18 men had beard/moustache and 15 other subjects had short facial hair. Conclusion: We developed and internally validated a minimum dataset for vascular access device research. This study generated new knowledge to enable healthcare systems to collect relevant, useful and meaningful vascular access data. Use of this standardised approach can help benchmark clinical practice and target improvements worldwide. Reference: Specs on Faces dataset (SoF) comprises 2,662 original images of size 640 × 480 pixels for 112 persons (66 males and 46 females) from different ages. The glasses are the common natural occlusion in all images of the dataset. This original set of images consists of two parts:Description WIDER FACE dataset is a face detection benchmark dataset, of which images are selected from the publicly available WIDER dataset. We choose 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion as depicted in the sample images. WIDER FACE dataset is organized based on 61 event classes. We want to build a robust and accurate face tracking system running in real-time, as shown in the Quicktime demo video (Realvideo encoded): Also we want to extend current single face tracking system to track multiple faces, even when there's occlusion between faces. Photometric Ambient Occlusion Daniel Hauagge Scott Wehrwein Kavita Bala Noah Snavely Cornell University fhauagge, swehrwein, kb, [email protected] Abstract We present a method for computing ambient occlusion (AO) for a stack of images of a scene from a fixed viewpoint. Ambient occlusion, a concept common in computer graph- of face recall with around 150 proposals, ˇ0.5% of full sliding windows, and ˇ10% of generic object proposals [19], measured on the FDDB dataset [20]). (3) Refining the face hypotheses – Both the aforementioned com-ponents offer a chance to find a face even under severe occlusion and pose variations. The output of these components is a small Dec 01, 2016 · Images of this new dataset can be used for evaluating facial image processing systems such as face recognition or facial age estimation under partially occlusion, especially that it contains four different facial occlusion. • Upper and lower face occlusion is one the main specific of this new dataset. Description WIDER FACE dataset is a face detection benchmark dataset, of which images are selected from the publicly available WIDER dataset. We choose 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion as depicted in the sample images. WIDER FACE dataset is organized based on 61 event classes. Jul 16, 2010 · Video Dataset for Occlusion/Object Boundary Detection This dataset of short video clips was developed and used for the following publications, as part of our continued research on detecting boundaries for segmentation and recognition. Please reference one or more of them (at least the IJCV article) if you use this dataset. The face image can have different types of occlusion viz. glasses, hand, paper, cap, cigarette, bottle, and cropping etc. Deep learning is used for classifying the face image into occluded image or the non-occluded image. The gender binary classification into male and female is presented on the two datasets. Oct 12, 2020 · One-stop occlusion, which is defined as the combination of atrial septal defect [ASD] or patent foramen ovale [PFO] occlusion and left atrial appendage [LAA] closure, in patients with ASD/PFO and atrial fibrillation (AF) has not yet been investigated systematically. This study aimed to evaluate the safety and efficacy of one-stop occlusion in the treatment of adult patients with ASD/PFO and AF ... Sep 14, 2020 · Experimental evaluations on the widely used CelebA dataset and a dataset with natural occlusions we collected show that the proposed approach can outperform the state of the art methods in natural face de-occlusion. Ground truth: electro_scan_raw.7z (0.6 GB) electro_scan_clean.7z (0.5 GB) electro_rig_scan_eval.7z (0.1 GB) electro_rig_occlusion.7z (0.1 GB) electro_rig_depth.7z (0.6 GB) electro_rig_stereo_pairs_gt.7z (0.9 GB) forest - 4*257 images outdoors forest_rig_undistorted.7z (0.4 GB) forest_rig.7z (0.5 GB) BACKGROUND AND PURPOSE: MR angiography (MRA) is increasingly used as a noninvasive imaging technique for the follow-up of coiled intracranial aneurysms. However, the need for contrast enhancement has not yet been elucidated. We compared 3D time-of-flight MRA (TOF-MRA) and contrast-enhanced MRA (CE-MRA) at 3T with catheter angiography. MATERIALS AND METHODS: Sixty-seven patients with 72 ... provided even under occlusion. The dataset is composed of images from new and existing datasets such as LFPW [18], HELEN [19], AFW [20], and 300-W face datasets with landmarks provided by the 300-W challenge [21][22][23]. The provided annotations from the 300-W datasets do not attempt to annotate every face in the image, so AFLW is The LSLF dataset is currently the largest labeled face image dataset in the literature in terms of the number of labeled images and the number of individuals compared to other existing face image datasets. Second, we introduced our CrowedFaces and CrowedNonFaces image datasets.May 05, 2016 · Our dataset comprised four prospective stroke registries including 7022 patients. Among them, 1610 (22.9%) had incomplete data and were excluded from the analysis. Among the 5412 (77.1%) patients (mean age 68.7 ± 13.9 years) who were finally included in the analysis, 3178 (58.7%) were males, and mean NIHSS was 9.0 ± 7.8. CUHK Occlusion Dataset . Download. CUHK occlusion data set is for research on activity analysis and crowded scenes. This dataset contains 1063 images with occluded pedestrians from the datasets of Caltech [1], ETHZ [2], TUD-Brussels [3], INRIA [4], Caviar [5] and images collected by us. Sep 14, 2020 · Experimental evaluations on the widely used CelebA dataset and a dataset with natural occlusions we collected show that the proposed approach can outperform the state of the art methods in natural face de-occlusion. Part based modeling could do the trick OR simply retrain a face model using a dataset that contains these smaller occlusions. Keep in mind that the supplied model has training data where people just look straight into the camera without a single obstruction. / 20 Multiple Perspectives, Instances, Sizes, Occlusions: 3 COCO Keypoints Dataset (I) • 17 types of keypoints. • 58,945 images. • 156,165 annotated people. Face Occlusion Dataset A normal face image consists of two eyes, a nose and a mouth. The geometrical and textual information from these components is critical to the recognition or identi¯- cation of a person. If any of these components is blocked or covered, the face image is considered to be occluded. In surveillance settings, cameras are usually placed far away from the subjects, thereby resulting in variations across pose, illumination, occlusion, and resolution. Current video datasets used for face recognition are often captured in constrained environments, and thus fail to simulate the real world scenarios. Oct 20, 2020 · Radial artery occlusion is a silent complication of a transradial approach to cardiac catheterization that may complicate subsequent transradial procedures in patients undergoing cardiac catheterization. A transradial band reduces vascular complications and provides brisk, powerful and effective haemostasis. The purpose of this study was to assess the frequency of radial artery occlusion in ... that face recognition operate on non-frontal images with uncontrolled lighting and non-compliant subjects, datasets were created with systematic variation in imaging condi-tions such as pose, lighting, expression, and occlusion in still and video images [11,13,22,29]. For each new dataset, successive methods were devised with increasing ... The Honda/UCSD Video Database contains two datasets. The first dataset is recorded by a SONY EVI-D30 camera at Honda Research Institute in 2002. It includes three different subsets, Training, Testing, and Occlusion Testing. Each subset contains 20, 42, 13 videos repectively from 20 human subjects.
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Many thanks to the kindly help from Rössler, Andreas and Nießner, Matthias, you can download the dataset with above link . With the dataset you can 1)compare your own face replacement method with FaceShifter qualitatively and quantitively, 2) develop and test state-of-the-art face forgery detection algorithm on the generated videos.

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  • occlusion edges as well as a benchmark dataset of human performance on a standard edge-detection problem studied in machine vision (Konishi et al., 2003; Martin et al., 2004; Zhou & Mel, 2008). Finally, we discuss possible mechanisms for natural occlusion detection and suggest directions for future research. Methods Image databases
  • Wider-face: 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion, organized based on 61 event classes: Download: 2015: AFW: AFW dataset is built using Flickr images. It has 205 images with 473 labeled faces. For each face, annotations include a rectangular bounding box, 6 landmarks and the pose ...

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/ 20 Multiple Perspectives, Instances, Sizes, Occlusions: 3 COCO Keypoints Dataset (I) • 17 types of keypoints. • 58,945 images. • 156,165 annotated people.

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  • segmentation datasets label a single two-dimensional region partition. Our annotation model, outlined in Figure2, captures the object-part-subpart decomposition, as well as the occlusion relationships (e.g. apple in front of jacket, glasses in front of face) present in the scene.
  • Oct 28, 2015 · Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention. It is due to availability of feasible technologies, including mobile solutions. Research in automatic face recognition has been conducted since the 1960s, but the problem is still largely unsolved. Last decade has provided significant progress in this area owing to ...

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In addition, the dataset includes 6 manually labeled landmark positions for every face: left eye, right eye, tip of the nose, left side of mouth, right side of mouth and the chin. Other information, such as gender, year of birth, ethnicity, glasses (whether a person wears glasses or not) and the time of each session are also available.

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Many thanks to the kindly help from Rössler, Andreas and Nießner, Matthias, you can download the dataset with above link . With the dataset you can 1)compare your own face replacement method with FaceShifter qualitatively and quantitively, 2) develop and test state-of-the-art face forgery detection algorithm on the generated videos.

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Our face dataset is designed to present faces in real-world conditions. Faces show large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (e.g. food, hands, microphones,
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The crowedFaces and CrowedNonFaces datasets include faces and non-faces images from crowed scenes. These datasets essentially aim for researchers to provide a large number of training examples with many variations for large scale face learning and face recognition tasks.

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It consists of 2,000 images, which are selected from open source web face dataset [8] and cover large variations of pose, expression and occlusion. The images without ground truth will be released on April 7, 2020. Test data. It contains 2,000 web face images as well.

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Mar 22, 2018 · Occlusion based methods attempt to answer this question by systematically occluding different portions of the input image with a grey square, and monitoring the output of the classifier. The examples clearly show the model is localizing the objects within the scene, as the probability of the correct class drops significantly when the object is ...

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