Uncalibrated Non-Rigid Factorisation by Independent Subspace Analysis

We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. The word general refers to an approach that recovers the non-rigid affine structure and motion from 2D point correspondences by assuming that (1) the non-rigid shapes are generated by a linear combination of rigid 3D basis shapes, (2) that the non-rigid shapes are affine in nature, i.e., they can be modelled as deviations from the mean, rigid shape, (3) and that the basis shapes are statistically independent. In contrast to the majority of existing works, no prior information is assumed for the structure and motion apart from the assumption the that underlying basis shapes are statistically independent. The independent 3D shape bases are recovered by independent subspace analysis (ISA). Likewise, in contrast to the most previous approaches, no calibration information is assumed for affine cameras; the reconstruction is solved up to a global affine ambiguity that makes our approach simple but efficient. In the experiments, we evaluated the method with several standard data sets including a real face expression data set of 7200 faces with 2D point correspondences and unknown 3D structure and motion for which we obtained promising results

TemPose: a new skeleton-based transformer model designed for fine-grained motion recognition in badminton

This paper presents TemPose, a novel skeleton-based transformer model designed for fine-grained motion recognition to improve understanding of the detailed player actions in badminton. The model utilizes multiple temporal and interaction layers to capture variable-length multi-person human actions while minimizing reliance on non-human visual context. TemPose is evaluated on two fine-grained badminton datasets, where it significantly outperforms other baseline models by incorporating additional input streams, such as the shuttlecock position, into the temporal transformer layers of the model. Additionally, TemPose demonstrates great versatility by achieving competitive results compared to other state-of-the-art skeleton-based models on the large-scale action recognition benchmark NTU RGB+D. Experiments are conducted to explore how different model parameter configurations affect TemPose's performance. Additionally, a qualitative analysis of the temporal attention maps suggests that the model learns to prioritize frames of specific poses relevant to different actions while formulating an intuition of each individual's importance in the sequences. Overall, TemPose is an intuitive and versatile architecture that has the potential to be further developed and incorporated into other methods for managing human motion in sports with state-of-the-art results.<br/

Tensor-based Subspace Factorization for StyleGAN

In this paper, we propose $\tau$GAN a tensor-based method for modeling the latent space of generative models. The objective is to identify semantic directions in latent space. To this end, we propose to fit a multilinear tensor model on a structured facial expression database, which is initially embedded into latent space. We validate our approach on StyleGAN trained on FFHQ using BU-3DFE as a structured facial expression database. We show how the parameters of the multilinear tensor model can be approximated by Alternating Least Squares. Further, we introduce a tacked style-separated tensor model, defined as an ensemble of style-specific models to integrate our approach with the extended latent space of StyleGAN. We show that taking the individual styles of the extended latent space into account leads to higher model flexibility and lower reconstruction error. Finally, we do several experiments comparing our approach to former work on both GANs and multilinear models. Concretely, we analyze the expression subspace and find that the expression trajectories meet at an apathetic face that is consistent with earlier work. We also show that by changing the pose of a person, the generated image from our approach is closer to the ground truth than results from two competing approaches.Comment: Accepted for FG202

Intramural Duodenal Haematoma after Endoscopic Biopsy: Case Report and Review of the Literature

The development of intramural duodenal haematoma (IDH) after small bowel biopsy is an unusual lesion and has only been reported in 18 children. Coagulopathy, thrombocytopenia and some special features of duodenal anatomy, e.g. relatively fixed position in the retroperitoneum and numerous submucosal blood vessels, have been suggested as a cause for IDH. The typical clinical presentation of IDH is severe abdominal pain and vomiting due to duodenal obstruction. In addition, it is often associated with pancreatitis and cholestasis. Diagnosis is confirmed using imaging techniques such as ultrasound, magnetic resonance imaging or computed tomography and upper intestinal series. Once diagnosis is confirmed and intestinal perforation excluded, conservative treatment with nasogastric tube and parenteral nutrition is sufficient. We present a case of massive IDH following endoscopic grasp forceps biopsy in a 5-year-old girl without bleeding disorder or other risk for IDH, which caused duodenal obstruction and mild pancreatitis and resolved within 2 weeks of conservative management. Since duodenal biopsies have become the common way to evaluate children or adults for suspected enteropathy, the occurrence of this complication is likely to increase. In conclusion, the review of the literature points out the risk for IDH especially in children with a history of bone marrow transplantation or leukaemia

Manganese in the shell of the bivalve Mytilus edulis: Seawater Mn or physiological control?

Manganese in the shell calcite of marine bivalves has been suggested to reflect ambient seawater Mn concentrations, thus providing a high-resolution archive of past seawater Mn concentrations. However, a quantitative relationship between seawater Mn and shell Mn/Ca ratios, as well as clear understanding of which process(es) control(s) shell Mn/Ca, are still lacking. Blue mussels, Mytilus edulis, were grown in a one-year duration field experiment in the Menai Strait, U.K., to study the relationship between seawater particulate and dissolved Mn2+ concentrations and shell calcite Mn/Ca ratios. Shell Mn/Ca showed a well-defined intra-annual double-peak, with maximum values during early spring and early summer and low values during autumn and winter. Seawater particulate Mn peaked during winter and autumn, with a series of smaller peaks during spring and summer, whereas dissolved Mn2+ exhibited a marked single maximum during late-spring to early-summer, being low during the remainder of the year. Consequently, neither seawater particulate Mn nor dissolved Mn2+ concentrations explain the intra-annual variation of shell Mn/Ca ratios. A physiological control on shell Mn/Ca ratios is evident from the strong similarity and timing of the double-peaked intra-annual variations of Mn/Ca and shell growth rate (SGR), the latter corresponding to periods of increased metabolic activity (as indicated by respiration rate). It is thus likely that in M. edulis SGR influences shell Mn/Ca by altering the concentration or activity of Mn2+ within the extra-pallial fluid (EPF), by changing the flux of Mn into or the proportion of protein bound Mn within the EPF. By linking shell Mn/Ca ratios to the endogenous and environmental factors that determine growth and metabolic activity, this study helps to explain the lack of a consistent relationship between shell Mn/Ca in marine bivalve shell calcite and seawater particulate and dissolved Mn2+ concentrations. The use of Mn content from M. edulis shell calcite as a proxy for the dissolved and/or particulate Mn concentrations, and thus the biogeochemical processes that control them, remains elusive

TemPose:a new skeleton-based transformer model designed for fine-grained motion recognition in badminton

This paper presents TemPose, a novel skeleton-based transformer model designed for fine-grained motion recognition to improve understanding of the detailed player actions in badminton. The model utilizes multiple temporal and interaction layers to capture variable-length multi-person human actions while minimizing reliance on non-human visual context. TemPose is evaluated on two fine-grained badminton datasets, where it significantly outperforms other baseline models by incorporating additional input streams, such as the shuttlecock position, into the temporal transformer layers of the model. Additionally, TemPose demonstrates great versatility by achieving competitive results compared to other state-of-the-art skeleton-based models on the large-scale action recognition benchmark NTU RGB+D. Experiments are conducted to explore how different model parameter configurations affect Tem-Pose's performance. Additionally, a qualitative analysis of the temporal attention maps suggests that the model learns to prioritize frames of specific poses relevant to different actions while formulating an intuition of each individual's importance in the sequences. Overall, TemPose is an intuitive and versatile architecture that has the potential to be further developed and incorporated into other methods for managing human motion in sports with state-of-the-art results.</p