Accretion of a Symmetry Breaking Scalar Field by a Schwarzschild Black Hole

We simulate the behaviour of a Higgs-like field in the vicinity of a Schwarzschild black hole using a highly accurate numerical framework. We consider both the limit of the zero-temperature Higgs potential, and a toy model for the time-dependent evolution of the potential when immersed in a slowly cooling radiation bath. Through these numerical investigations, we aim to improve our understanding of the non-equilibrium dynamics of a symmetry breaking field (such as the Higgs) in the vicinity of a compact object such as a black hole. Understanding this dynamics may suggest new approaches for studying properties of scalar fields using black holes as a laboratory.Comment: 16 pages, 5 figure

Assessment criteria for 2D shape transformations in animation

The assessment of 2D shape transformations (or morphing) for animation is a difficult task because it is a multi-dimensional problem. Existing morphing techniques pay most attention to shape information interactive control and mathematical simplicity. This paper shows that it is not enough to use shape information alone, and we should consider other factors such as structure, dynamics, timing, etc. The paper also shows that an overall objective assessment of morphing is impossible because factors such as timing are related to subjective judgement, yet local objective assessment criteria, e.g. based on shape, are available. We propose using “area preservation” as the shape criterion for the 2D case as an acceptable approximation to “volume preservation” in reality, and use it to establish cases in which a number of existing techniques give clearly incorrect results. The possibility of deriving objective assessment criteria for dynamics simulations and timing under certain conditions is discussed

Comparing and Evaluating Real Time Character Engines for Virtual Environments

As animated characters increasingly become vital parts of virtual environments, then the engines that drive these characters increasingly become vital parts of virtual environment software. This paper gives an overview of the state of the art in character engines, and proposes a taxonomy of the features that are commonly found in them. This taxonomy can be used as a tool for comparison and evaluation of different engines. In order to demonstrate this we use it to compare three engines. The first is Cal3D, the most commonly used open source engine. We also introduce two engines created by the authors, Piavca and HALCA. The paper ends with a brief discussion of some other popular engines

Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition

A dramatic increase in real-world video volume with extremely diverse and emerging topics naturally forms a long-tailed video distribution in terms of their categories, and it spotlights the need for Video Long-Tailed Recognition (VLTR). In this work, we summarize the challenges in VLTR and explore how to overcome them. The challenges are: (1) it is impractical to re-train the whole model for high-quality features, (2) acquiring frame-wise labels requires extensive cost, and (3) long-tailed data triggers biased training. Yet, most existing works for VLTR unavoidably utilize image-level features extracted from pretrained models which are task-irrelevant, and learn by video-level labels. Therefore, to deal with such (1) task-irrelevant features and (2) video-level labels, we introduce two complementary learnable feature aggregators. Learnable layers in each aggregator are to produce task-relevant representations, and each aggregator is to assemble the snippet-wise knowledge into a video representative. Then, we propose Minority-Oriented Vicinity Expansion (MOVE) that explicitly leverages the class frequency into approximating the vicinity distributions to alleviate (3) biased training. By combining these solutions, our approach achieves state-of-the-art results on large-scale VideoLT and synthetically induced Imbalanced-MiniKinetics200. With VideoLT features from ResNet-50, it attains 18% and 58% relative improvements on head and tail classes over the previous state-of-the-art method, respectively.Comment: Accepted to AAAI 2023. Code is available at https://github.com/wjun0830/MOV

Accretion of a symmetry-breaking scalar field by a Schwarzschild black hole

We simulate the behaviour of a Higgs-like field in the vicinity of a Schwarzschild black hole using a highly accurate numerical framework. We consider both the limit of the zero-temperature Higgs potential and a toy model for the time-dependent evolution of the potential when immersed in a slowly cooling radiation bath. Through these numerical investigations, we aim to improve our understanding of the non-equilibrium dynamics of a symmetry-breaking field (such as the Higgs) in the vicinity of a compact object such as a black hole. Understanding this dynamics may suggest new approaches for studying properties of scalar fields using black holes as a laboratory

Activity of nAChRs containing α9 subunits modulates synapse stabilization via bidirectional signaling programs

Although the synaptogenic program for cholinergic synapses of the neuromuscular junction is well known, little is known of the identity or dynamic expression patterns of proteins involved in non-neuromuscular nicotinic synapse development. We have previously demonstrated abnormal presynaptic terminal morphology following loss of nicotinic acetylcholine receptor (nAChR) α9 subunit expression in adult cochleae. However, the molecular mechanisms underlying these changes have remained obscure. To better understand synapse formation and the role of cholinergic activity in the synaptogenesis of the inner ear, we exploit the nAChR α9 subunit null mouse. In this mouse, functional acetylcholine (ACh) neurotransmission to the hair cells is completely silenced. Results demonstrate a premature, effusive innervation to the synaptic pole of the outer hair cells in α9 null mice coinciding with delayed expression of cell adhesion proteins during the period of effusive contact. Collapse of the ectopic innervation coincides with an age-related hyperexpression pattern in the null mice. In addition, we document changes in expression of presynaptic vesicle recycling/trafficking machinery in the α9 null mice that suggests a bidirectional information flow between the target of the neural innervation (the hair cells) and the presynaptic terminal that is modified by hair cell nAChR activity. Loss of nAChR activity may alter transcriptional activity, as CREB binding protein expression is decreased coincident with the increased expression of N-Cadherin in the adult α9 null mice. Finally, by using mice expressing the nondesensitizing α9 L90T point mutant nAChR subunit, we show that increased nAChR activity drives synaptic hyperinnervation. © 2009 Wiley Periodicals, Inc.Fil: Murthy, Vidya. Tufts University School of Medicine; EslovaquiaFil: Taranda, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. Tufts University School of Medicine; EslovaquiaFil: Elgoyhen, Ana Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Farmacología; ArgentinaFil: Vetter, Douglas E.. Tufts University School of Medicine; Eslovaqui

SMPLicit: Topology-aware Generative Model for Clothed People

In this paper we introduce SMPLicit, a novel generative model to jointly represent body pose, shape and clothing geometry. In contrast to existing learning-based approaches that require training specific models for each type of garment, SMPLicit can represent in a unified manner different garment topologies (e.g. from sleeveless tops to hoodies and to open jackets), while controlling other properties like the garment size or tightness/looseness. We show our model to be applicable to a large variety of garments including T-shirts, hoodies, jackets, shorts, pants, skirts, shoes and even hair. The representation flexibility of SMPLicit builds upon an implicit model conditioned with the SMPL human body parameters and a learnable latent space which is semantically interpretable and aligned with the clothing attributes. The proposed model is fully differentiable, allowing for its use into larger end-to-end trainable systems. In the experimental section, we demonstrate SMPLicit can be readily used for fitting 3D scans and for 3D reconstruction in images of dressed people. In both cases we are able to go beyond state of the art, by retrieving complex garment geometries, handling situations with multiple clothing layers and providing a tool for easy outfit editing. To stimulate further research in this direction, we will make our code and model publicly available at http://www.iri.upc.edu/people/ecorona/smplicit/.Comment: Accepted at CVPR 202

HeadOn: Real-time Reenactment of Human Portrait Videos

We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel real-time reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.Comment: Video: https://www.youtube.com/watch?v=7Dg49wv2c_g Presented at Siggraph'1