Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction

Current 6D object pose methods consist of deep CNN models fully optimized for a single object but with its architecture standardized among objects with different shapes. In contrast to previous works, we explicitly exploit each object's distinct topological information i.e. 3D dense meshes in the pose estimation model, with an automated process and prior to any post-processing refinement stage. In order to achieve this, we propose a learning framework in which a Graph Convolutional Neural Network reconstructs a pose conditioned 3D mesh of the object. A robust estimation of the allocentric orientation is recovered by computing, in a differentiable manner, the Procrustes' alignment between the canonical and reconstructed dense 3D meshes. 6D egocentric pose is then lifted using additional mask and 2D centroid projection estimations. Our method is capable of self validating its pose estimation by measuring the quality of the reconstructed mesh, which is invaluable in real life applications. In our experiments on the LINEMOD, OCCLUSION and YCB-Video benchmarks, the proposed method outperforms state-of-the-arts

On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks

Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks. These are typically not compared nor discussed in the literature due to a lack of multi-modal datasets. Texture-less regions are problematic for structure from motion and stereo, reflective material poses issues for active sensing, and distances for translucent objects are intricate to measure with existing hardware. Training on inaccurate or corrupt data induces model bias and hampers generalisation capabilities. These effects remain unnoticed if the sensor measurement is considered as ground truth during the evaluation. This paper investigates the effect of sensor errors for the dense 3D vision tasks of depth estimation and reconstruction. We rigorously show the significant impact of sensor characteristics on the learned predictions and notice generalisation issues arising from various technologies in everyday household environments. For evaluation, we introduce a carefully designed dataset\footnote{dataset available at https://github.com/Junggy/HAMMER-dataset} comprising measurements from commodity sensors, namely D-ToF, I-ToF, passive/active stereo, and monocular RGB+P. Our study quantifies the considerable sensor noise impact and paves the way to improved dense vision estimates and targeted data fusion.Comment: Accepted at CVPR 2023, Main Paper + Supp. Mat. arXiv admin note: substantial text overlap with arXiv:2205.0456

MUCKE Participation at Retrieving Diverse Social Images Task of MediaEval 2013

The Mediaeval 2013 Retrieving Diverse Social Image Task addresses the challenge of improving both relevance and diversity of photos in a retrieval task on Flickr. We propose a clustering based technique that exploits both textual and visual information. We introduce a k-Nearest Neighbor (k-NN) inspired re-ranking algorithm that is applied before clustering to clean the dataset. After the clustering step, we exploit social cues to rank clusters by social relevance. From those ranked clusters images are retrieved according to their distance to cluster centroids. 1

Antibiotic treatment outcomes in community-acquired pneumonia

WOS: 000441766000006PubMed ID: 30119147Background/aim: The optimal empiric antibiotic regimen for patients with community-acquired pneumonia (CAP) remains unclear. This study aimed to evaluate the clinical cure rate, mortality, and length of stay among patients hospitalized with community-acquired pneumonia in nonintensive care unit (ICU) wards and treated with a beta-lactam, beta-lactam and macrolide combination, or a fluoroquinolone. Materials and methods: This prospective cohort study was perfbrined using standardized web-based database sheets from January 2009 to September 2013 in nine tertiary care hospitals in Turkey. Results: Six hundred and twenty-one consecutive patients were enrolled. A pathogen was identified in 78 (12.6%) patients. The most frequently isolated bacteria were S. pneumoniae (21.8%) and P. aeruginosa (19.2%). The clinical cure rate and length of stay were not different among patients treated with beta-lactam, beta-lactam and macrolide combination, and fluoroquinolone. Forty-seven patients (9.2%) died during the hospitalization period. There was no difference in survival among the three treatment groups. Conclusion: In patients admitted to non-ICU hospital wards for CAP, there was no difference in clinical outcomes between beta-lactam, beta-lactam and macrolide combination, and fluoroquinolone regimens.Turk Toraks DernegiThis study was supported by a grant from the Turk Toraks Dernegi. We thank the TURCAP Study Group (Kokturk N, Filiz A, Edis EC, Uzaslan E, Yalcinsoy M, Gunduz C, Dikensoy O, Cetinkaya C, Durmaz F) for their valuable contributions

A Retrospective Evaluation of the Epithelial Changes/Lesions and Neoplasms of the Gallbladder in Turkey and a Review of the Existing Sampling Methods: A Multicentre Study

Objective: As there is continuing disagreement among the observers on the differential diagnosis between the epithelial changes/lesions and neoplasms of the gallbladder, this multicentre study was planned in order to assess the rate of the epithelial gallbladder lesions in Turkey and to propose microscopy and macroscopy protocols. Material and Method: With the participation of 22 institutions around Turkey that were included in the Hepato-Pancreato-Biliary Study Group, 89,324 cholecystectomy specimens sampled from 2003 to 2016 were retrospectively evaluated. The numbers of adenocarcinomas, dysplasias, intracholecystic neoplasms/adenomas, intestinal metaplasias and reactive atypia were identified with the review of pathology reports and the regional and countrywide incidence rates were presented in percentages. Results: Epithelial changes/lesions were reported in 6% of cholecystectomy materials. Of these epithelial lesions, 7% were reported as adenocarcinoma, 0.9% as high-grade dysplasia, 4% as low-grade dysplasia, 7.8% as reactive/regenerative atypia, 1.7% as neoplastic polyp, and 15.6% as intestinal metaplasia. The remaining lesions (63%) primarily included non-neoplastic polypoids/hyperplastic lesions and antral/pyloric metaplasia. There were also differences between pathology laboratories. Conclusion: The major causes of the difference in reporting these epithelial changes/lesions and neoplasms include the differences related to the institute's oncological surgery frequency, sampling protocols, geographical dissimilarities, and differences in the diagnoses/interpretations of the pathologists. It seems that the diagnosis may change if new sections are taken from the specimen when any epithelial abnormality is seen during microscopic examination of the cholecystectomy materials

Analysis of Outcomes in Ischemic vs Nonischemic Cardiomyopathy in Patients With Atrial Fibrillation A Report From the GARFIELD-AF Registry

IMPORTANCE Congestive heart failure (CHF) is commonly associated with nonvalvular atrial fibrillation (AF), and their combination may affect treatment strategies and outcomes