Unsupervised 3D Pose Estimation with Geometric Self-Supervision

We present an unsupervised learning approach to recover 3D human pose from 2D skeletal joints extracted from a single image. Our method does not require any multi-view image data, 3D skeletons, correspondences between 2D-3D points, or use previously learned 3D priors during training. A lifting network accepts 2D landmarks as inputs and generates a corresponding 3D skeleton estimate. During training, the recovered 3D skeleton is reprojected on random camera viewpoints to generate new "synthetic" 2D poses. By lifting the synthetic 2D poses back to 3D and re-projecting them in the original camera view, we can define self-consistency loss both in 3D and in 2D. The training can thus be self supervised by exploiting the geometric self-consistency of the lift-reproject-lift process. We show that self-consistency alone is not sufficient to generate realistic skeletons, however adding a 2D pose discriminator enables the lifter to output valid 3D poses. Additionally, to learn from 2D poses "in the wild", we train an unsupervised 2D domain adapter network to allow for an expansion of 2D data. This improves results and demonstrates the usefulness of 2D pose data for unsupervised 3D lifting. Results on Human3.6M dataset for 3D human pose estimation demonstrate that our approach improves upon the previous unsupervised methods by 30% and outperforms many weakly supervised approaches that explicitly use 3D data

Zu einer vernachlässigten Dimension postsozialistischer Transformation: (Re-)Modernisierung als Fremdheitsverhältnis

"Bei der Entstehung der neuen Wirtschafts- und Gesellschaftsordnung in den postsozialistischen Ländern handelt es sich um die Umverteilung von Reichtum, der in der Gewalt des Staates war. Lediglich durch diese Umverteilung ist die Entstehung der neuen Eliten möglich. Deshalb stehen die Umgestaltungsmuster betrieblicher Sozialorganisation einerseits und ihre Auswirkungen auf die o.a. Umverteilung andererseits im Mittelpunkt unseres Forschungsinteresses. In einer von der Volkswagen-Stiftung geförderten empirischen Studie zu den betrieblichen Transformationsmustern in Polen, Ungarn und Bulgarien sind wir u.a. diesen Fragen nachgegangen. Interviewt wurden über 100 Vertreter der Unternehmensleitungen und der Interessenvertretungen der Beschäftigten in zwei Wellen(1993 und 1994). Nicht die offizielle Übertragung der Eigentumsrechte ist der ausschlaggebende Mechanismus der Umwandlung der Gesellschafts- und Wirtschaftsordnung, sondern - so die hier vertretene These - die schleichende Diffusion des staatlichen und des privaten Eigentums. Die offiziellen Formen der Privatisierung (die u.E. eine relativ marginale Rolle im Transformationsprozeß spielen) legalisieren entweder die bereits erfolgten Umverteilungsprozesse oder bereiten die weitere Konzentration des Eigentums in den sich in einer Konsolidierungsphase befindenden Zentren der ökonomischen Macht vor. Da das private Kapital überwiegend als Handelskapital fungiert, erfolgt dieser Prozeß in erster Linie durch die 'Kolonisierung' der Beziehungen der Unternehmen zu der relevanten Umwelt (Lieferungen, Kreditierung, Absatz usw.). Die primäre Akkumulation des Kapitals in den postsozialistischen Gesellschaften vollzieht sich vor allem durch den Transfer von Mehrwert, der in staatlichen Unternehmen hergestellt worden ist, in den privaten Sektor. Der Verlauf dieses Prozesses hängt im wesentlichen von den Mustern der innenorganisatorischen Integration ab. Wenn diese auch dem Modell des 'Clans' entsprechen, d.h. auf Vergemeinschaftung basieren und Vertrauensbeziehungen darstellen, werden eine 'Rückendeckung' durch die Belegschaft und dadurch Handlungsfreiräume für die postsozialistische 'Revolution der Manager' gewährleistet. Wenn - im Gegenteil - formale Macht das ausschlaggebende Integrationsmedium darstellt (Manchester-Kapitalismus, geraten die Manager unter Legitimationsdruck. Die daraus resultierende öffentliche Problematisierung der Beziehungen des Unternehmens zu den Kooperationspartnern stellt eine Bedrohung für die Handlungsfähigkeit des Manager-Clans dar mit allen daraus folgenden personellen und organisatorischen Konsequenzen. Die vorliegenden Forschungsergebnisse bilden eine Grundlage für die Diskussion über die Chancen des Clan-Modells in den postsozialistischen Gesellschaften und können von paradigmatischer Bedeutung für die organisationssoziologische Transformationsforschung sein." (Autorenreferat

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

A hallmark of the deep learning era for computer vision is the successful use of large-scale labeled datasets to train feature representations for tasks ranging from object recognition and semantic segmentation to optical flow estimation and novel view synthesis of 3D scenes. In this work, we aim to learn dense discriminative object representations for low-shot category recognition without requiring any category labels. To this end, we propose Deep Object Patch Encodings (DOPE), which can be trained from multiple views of object instances without any category or semantic object part labels. To train DOPE, we assume access to sparse depths, foreground masks and known cameras, to obtain pixel-level correspondences between views of an object, and use this to formulate a self-supervised learning task to learn discriminative object patches. We find that DOPE can directly be used for low-shot classification of novel categories using local-part matching, and is competitive with and outperforms supervised and self-supervised learning baselines. Code and data available at https://github.com/rehg-lab/dope_selfsup.Comment: Accepted at NeurIPS 2022. Code and data available at https://github.com/rehg-lab/dope_selfsu

Does Continual Learning = Catastrophic Forgetting?

Continual learning is known for suffering from catastrophic forgetting, a phenomenon where earlier learned concepts are forgotten at the expense of more recent samples. In this work, we challenge the assumption that continual learning is inevitably associated with catastrophic forgetting by presenting a set of tasks that surprisingly do not suffer from catastrophic forgetting when learned continually. We provide evidence that these reconstruction-type tasks exhibit positive forward transfer and that single-view 3D shape reconstruction improves the performance on learned and novel categories over time. We provide the novel analysis of knowledge transfer ability by looking at the output distribution shift across sequential learning tasks. Finally, we show that the robustness of these tasks leads to the potential of having a proxy representation learning task for continual classification. The codebase, dataset, and pre-trained models released with this article can be found at https://github.com/rehg-lab/CLRec

ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-based Consistency

We present ShapeClipper, a novel method that reconstructs 3D object shapes from real-world single-view RGB images. Instead of relying on laborious 3D, multi-view or camera pose annotation, ShapeClipper learns shape reconstruction from a set of single-view segmented images. The key idea is to facilitate shape learning via CLIP-based shape consistency, where we encourage objects with similar CLIP encodings to share similar shapes. We also leverage off-the-shelf normals as an additional geometric constraint so the model can learn better bottom-up reasoning of detailed surface geometry. These two novel consistency constraints, when used to regularize our model, improve its ability to learn both global shape structure and local geometric details. We evaluate our method over three challenging real-world datasets, Pix3D, Pascal3D+, and OpenImages, where we achieve superior performance over state-of-the-art methods.Comment: Accepted to CVPR 2023, project website at https://zixuanh.com/projects/shapeclipper.htm

Profile of blood cells and inflammatory mediators in periodic fever, aphthous stomatitis, pharyngitis and adenitis (PFAPA) syndrome

<p>Abstract</p> <p>Background</p> <p>This study aimed to profile levels of blood cells and serum cytokines during afebrile and febrile phases of periodic fever, aphthous <b>s</b>tomatitis, pharyngitis and adenitis (PFAPA) syndrome to advance pathophysiological understanding of this pediatric disease.</p> <p>Methods</p> <p>A cohort of patients with a median age of 4.9 years experiencing 'typical PFAPA' episodes participated in this study. Blood cells and serum cytokines were analyzed by CBC analysis and multiplex ELISA.</p> <p>Results</p> <p>Oscillations in the concentration of blood cells during the afebrile and febrile phases of typical PFAPA syndrome were observed; novel findings include increased monocytes and decreased eosinophils during a febrile episode and increased thrombocytes in the afebrile interval. Relatively modest levels of pro-inflammatory cytokines were present in sera. IFNγ-induced cytokine IP10/CXCL10 was increased after the onset of fever while T cell-associated cytokines IL7 and IL17 were suppressed during afebrile and febrile periods.</p> <p>Conclusions</p> <p>Identification of dysregulated blood cells and serum cytokines is an initial step towards the identification of biomarkers of PFAPA disease and/or players in disease pathogenesis. Future investigations are required to conclusively discern which mediators are associated specifically with PFAPA syndrome.</p

An examination of the factorial and convergent validity of four measures of conspiracist ideation, with recommendations for researchers

A number scales have been developed to measure conspiracist ideation, but little attention has been paid to the factorial validity of these scales. We reassessed the psychometric properties of four widely-used scales, namely the Belief in Conspiracy Theories Inventory (BCTI), the Conspiracy Mentality Questionnaire (CMQ), the Generic Conspiracist Beliefs Scale (GCBS), and the One-Item Conspiracy Measure (OICM). Eight-hundred-and-three U. S. adults completed all measures, along with measures of endorsement of 9/11 and anti- vaccination conspiracy theories. Through both exploratory and confirmatory factor analysis, we found that only the BCTI had acceptable factorial validity. We failed to confirm the factor structures of the CMQ and the GBCS, suggesting these measures had poor factorial valid- ity. Indices of convergent validity were acceptable for the BCTI, but weaker for the other measures. Based on these findings, we provide suggestions for the future refinement in the measurement of conspiracist ideation

Medulloblastoma Exome Sequencing Uncovers Subtype-Specific Somatic Mutations

Medulloblastomas are the most common malignant brain tumors in children1. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles2–5. Here, we utilized whole exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, novel findings in medulloblastoma. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma