ShantanuT01/DACTYL-Pretraining huggingface dataset:
Deep image inpainting aims to restore damaged or missing regions in an image with realistic contents. While having a wide range of applications such as object removal and image recovery, deep inpainting techniques also have the risk of being manipulated for image forgery. A promising countermeasure against such forgeries is deep inpainting detection, which aims to locate the inpainted regions in an image. In this paper, we make the first attempt towards universal detection of deep inpainting, where the detection network can generalize well when detecting different deep inpainting methods. To this end, we first propose a novel data generation approach to generate a universal training dataset, which imitates the noise discrepancies exist in real versus inpainted image contents to train universal detectors. We then design a Noise-Image Cross-fusion Network (NIX-Net) to effectively exploit the discriminative information contained in both the images and their noise patterns. We empirically show, on multiple benchmark datasets, that our approach outperforms existing detection methods by a large margin and generalize well to unseen deep inpainting techniques. Our universal training dataset can also significantly boost the generalizability of existing detection methods.
From a transfer formula in multivariate finite operator calculus, comes an expansion for the determinant similar to Ryser's formula for the permanent. Although this one contains many more terms than the usual determinant formula. To prove it, we consider the poset of ordered partitions, properties of the permutahedron, and some good old fashioned combinatorial techniques.
Person re-identification (ReID) is an important problem in computer vision, especially for video surveillance applications. The problem focuses on identifying people across different cameras or across different frames of the same camera. The main challenge lies in identifying the similarity of the same person against large appearance and structure variations, while differentiating between individuals. Recently, deep learning networks with triplet loss have become a common framework for person ReID. However, triplet loss focuses on obtaining correct orders on the training set. We demonstrate that it performs inferior in a clustering task. In this paper, we design a cluster loss, which can lead to the model output with a larger inter-class variation and a smaller intra-class variation compared to the triplet loss. As a result, our model has a better generalization ability and can achieve higher accuracy on the test set especially for a clustering task. We also introduce a batch hard training mechanism for improving the results and faster convergence of training.
It has been recently empirically established that some of the directly observed pa- rameters of GRBs are correlated with their important intrinsic parameters, like the luminosity or the total radiated energy. These correlations were derived, tested and used to standardize GRBs, i.e., to derive their luminosity or radiated energy from one or more observables, in order to construct an estimated fiducial Hubble diagram, assuming that radiation propagates in the standard LambdaCDM cosmological model. We extend these analyses by considering more general models of dark energy, and an updated data set of high redshift GRBs. We show that the correlation parameters only weakly depend on the cosmological model. Moreover we apply a local regression technique to estimate, in a model independent way, the distance modulus from the recently updated SNIa sample containing 307 SNIa (Astier et al. 2006), in order to calibrate the GRBs 2D correlations, considering only GRBs with z <1.4. The derived calibration parameters are used to construct a new GRBs Hubble diagram, which we call the calibrated GRBs HD. We also compare the estimated and calibrated GRBs HDs. It turns out that for the common GRBs they are fully statistically consistent, thus indicating that both of them are not affected by any systematic bias induced by the different standardizing procedures. We finally apply our methods to calibrate 95 long GRBs with the well-known Amati relation and construct the estimated and calibrated GRBs Hubble diagram that extends to redshifts z ~ 8. Even in this case there is consistency between these datasets. This means that the high redshift GRBs can be used to test different models of dark energy. We used the calibrated GRBs HD to constrain our quintessential cosmological model and derived the likelihood values of Omega_m and w(0).
We establish quasimodularity for a family of residual crank generating functions defined on overpartitions. We also show that the second moments of these $k$th residual cranks admit a combinatoric interpretation as weighted overpartition counts.
The mechanism of enhanced superconductivity in the one unit-cell (1UC) FeSe film on a SrTiO3 (STO) substrate has stimulated significant research interest but remains elusive. Using low-temperature, voltage-gated Raman spectroscopy and low-temperature valence electron energy loss spectroscopy (VEELS), we characterize the phonon behavior and interfacial charge transfer in single- and few-layer FeSe films on STO. Raman measurements reveal ambipolar softening of the FeSe vibrational modes, mimicking that of the underlying STO substrate. We attribute this behavior to an interfacial coupling effect of STO on FeSe lattice dynamics. This interfacial coupling effect is further supported by local electron effective mass enhancement, which is determined from the red-shift in the FeSe VEELS spectrum near the FeSe/STO interface. Our work sheds light on the possible interfacial mechanisms contributing to the enhanced superconductivity across the FeSe/STO interface and further unveils the potential of low-temperature gated Raman spectroscopy and VEELS in clarifying a broad category of quantum materials.
We report a possible detection of a 55-day X-ray modulation for the ultraluminous accreting pulsar M82 X-2 from archival Chandra observations. Because M82 X-2 is known to have a 2.5-day orbital period, if the 55-day period is real, it will be the superorbital period of the system. We also investigated variabilities of other three nearby ultraluminous X-ray sources in the central region of M82 with the Chandra data and did not find any evidence of periodicities. Furthermore, we re-examined the previously reported 62-day periodicity near the central region of M82 by performing a systematic timing study with all the archival Rossi X-Ray Timing Explorer and Swift data. Using various dynamic timing analysis methods, we confirmed that the 62-day period is not stable, suggesting that it is not the orbital period of M82 X-1 in agreement with previous work.
We present calculations of the charge density profile, subband occupancy and ellipsometry spectra of the electron gas at the LaAlO3/SrTiO3 interface. The calculations employ self-consistent Hartree and random phase approximations, a tight binding parametrization of the band structure and a model for the optical phonon of SrTiO3. The dependence of the spatial structure and occupancy of subbands on the magnitude of the polarization charge at the interface and the dielectric function is determined. The interface-confined subbands may be labelled by the symmetry (xy, xz, or yz) of the Ti d-orbitals from which they mainly derive. The xy-derived band nearest the interface contains the major proportion of the electronic charge, but a large number of more distant, slightly occupied xy-derived bands are also found. Depending on the magnitude of the polarization charge, zero, one, or two xz/yz derived subbands are found. When present, these xz/yz bands give the dominant contribution to the long-distance tail of the interface charge. The response to applied ac electric fields polarized parallel and perpendicular to the interface is calculated and the results are presented in terms of ellipsometry angles. Two features are found: a dip in the spectrum near the LO feature of the STO phonon and a peak at the higher energy. We show that the form and magnitude of the dip is related to the Drude response of carriers moving in the plane of the interface while the peak arises from the plasmon excitation of the xz and yz electrons. The relation of the features of the subband occupancies and the in-plane conductivities is given.
We propose a reduced form of spectral boundary conditions for holding fermions in the bag in a chiral invariant way. Our boundary conditions do not depend on time and allow Hamiltonian treatment of the system. They are suited for studies of chiral phenomena both in Minkowski and Euclidean spaces.
The growth of Jovian mass planets during migration in their protoplanetary disks is one of the most important problems that needs to be solved in light of observations of the exosolar planets. Studies of the migration of planets in standard gas disk models routinely show that migration is too fast to form Jovian planets, and that such migrating planetary cores generally plunge into the central stars in less than a Myr. In previous work, we have shown that a poorly ionized, less viscous region in a protoplanetary disk called a dead zone slows down the migration of fixed-mass planets. In this paper, we extend our numerical calculations to include dead zone evolution along with the disk, as well as planet formation via accretion of rocky and gaseous materials. Using our symplectic-integrator-gas dynamics code, we find that dead zones, even in evolving disks wherein migrating planets grow by accretion, still play a fundamental role in saving planetary systems. We demonstrate that Jovian planets form within 2.5 Myr for disks that are ten times more massive than a minimum mass solar nebula (MMSN) with an opacity reduction and without slowing down migration artificially. Our simulations indicate that protoplanetary disks with an initial mass comparable to the MMSN only produce Neptunian mass planets. We also find that planet migration does not help core accretion as much in the oligarchic planetesimal accretion scenario as it was expected in the runaway accretion scenario. Therefore we expect that an opacity reduction (or some other mechanisms) is needed to solve the formation timescale problem even for migrating protoplanets, as long as we consider the oligarchic growth. We also point out a possible role of a dead zone in explaining long-lived, strongly accreting gas disks.
We study two competing growth models. Each of these models describes the spread of a finite number of infections on a graph. Each infection evolves like an (oriented or unoriented) first passage percolation process except that once a vertex is infected by type $i$ infection, it remains of type $i$ forever. We give results about the shape of the area ultimately infected by the different infections.
We derive the form of reciprocal generalized radiative transfer (RGRT) that includes the Levermore-Pomraning attenuation law for paths leaving a deterministic origin. The resulting model describes linear transport within multi-dimensional stochastic binary mixtures with Markovian mixing statistics and nonstochastic albedo and phase function. The derivation includes a new attenuation law and related free-path distribution between collisions, which was previously estimated using a Monte Carlo approach. We also show that previous stationary descriptions of binary mixtures with binomial mixing statistics reduce to exponential attenuations and, thus, have an exact homogenization within classical radiative transfer.
We provide new, high-resolution A(Ks) extinction maps of the heavily reddened Galactic midplane based on the Rayleigh-Jeans Color Excess ("RJCE") method. RJCE determines star-by-star reddening based on a combination of near- and mid-infrared photometry. The new RJCE-generated maps have 2 x 2 arcmin pixels and span some of the most severely extinguished regions of the Galaxy -- those covered with Spitzer+IRAC imaging by the GLIMPSE-I, -II, -3D, and Vela-Carina surveys, from 256<l<65 deg and, in general, for |b| <= 1-1.5 deg (extending up to |b|<=4 deg in the bulge). Using RJCE extinction measurements, we generate dereddened color-magnitude diagrams and, in turn, create maps based on main sequence, red clump, and red giant star tracers, each probing different distances and thereby providing coarse three-dimensional information on the relative placement of dust cloud structures. The maps generated from red giant stars, which reach to ~18-20 kpc, probe beyond most of the Milky Way extinction in most directions and provide close to a "total Galactic extinction" map -- at minimum they provide high angular resolution maps of lower limits on A(Ks). Because these maps are generated directly from measurements of reddening by the very dust being mapped, rather than inferred on the basis of some less direct means, they are likely the most accurate to date for charting in detail the highly patchy differential extinction in the Galactic midplane. We provide downloadable FITS files and an IDL tool for retrieving extinction values for any line of sight within our mapped regions.
A map which is non-orientable or has non-empty boundary has a canonical double cover which is orientable and has empty boundary. The map is called stable if every automorphism of this cover is a lift of an automorphism of the map. This note describes several infinite families of unstable maps, and relates them to similar phenomena for graphs, hypermaps and Klein surfaces.
Purpose: Segmentation of organs-at-risk (OARs) is a bottleneck in current radiation oncology pipelines and is often time consuming and labor intensive. In this paper, we propose an atlas-based semi-supervised registration algorithm to generate accurate segmentations of OARs for which there are ground truth contours and rough segmentations of all other OARs in the atlas. To the best of our knowledge, this is the first study to use learning-based registration methods for the segmentation of head and neck patients and demonstrate its utility in clinical applications. Methods: Our algorithm cascades rigid and deformable deformation blocks, and takes on an atlas image (M), set of atlas-space segmentations (S_A), and a patient image (F) as inputs, while outputting patient-space segmentations of all OARs defined on the atlas. We train our model on 475 CT images taken from public archives and Stanford RadOnc Clinic (SROC), validate on 5 CT images from SROC, and test our model on 20 CT images from SROC. Results: Our method outperforms current state of the art learning-based registration algorithms and achieves an overall dice score of 0.789 on our test set. Moreover, our method yields a performance comparable to manual segmentation and supervised segmentation, while solving a much more complex registration problem. Whereas supervised segmentation methods only automate the segmentation process for a select few number of OARs, we demonstrate that our methods can achieve similar performance for OARs of interest, while also providing segmentations for every other OAR on the provided atlas. Conclusions: Our proposed algorithm has significant clinical applications and could help reduce the bottleneck for segmentation of head and neck OARs. Further, our results demonstrate that semi-supervised diffeomorphic registration can be accurately applied to both registration and segmentation problems.
Tracking often uses a multi-stage pipeline of feature extraction, target information integration, and bounding box estimation. To simplify this pipeline and unify the process of feature extraction and target information integration, we present a compact tracking framework, termed as MixFormer, built upon transformers. Our core design is to utilize the flexibility of attention operations, and propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration. This synchronous modeling scheme allows to extract target-specific discriminative features and perform extensive communication between target and search area. Based on MAM, we build our MixFormer tracking framework simply by stacking multiple MAMs with progressive patch embedding and placing a localization head on top. In addition, to handle multiple target templates during online tracking, we devise an asymmetric attention scheme in MAM to reduce computational cost, and propose an effective score prediction module to select high-quality templates. Our MixFormer sets a new state-of-the-art performance on five tracking benchmarks, including LaSOT, TrackingNet, VOT2020, GOT-10k, and UAV123. In particular, our MixFormer-L achieves NP score of 79.9% on LaSOT, 88.9% on TrackingNet and EAO of 0.555 on VOT2020. We also perform in-depth ablation studies to demonstrate the effectiveness of simultaneous feature extraction and information integration. Code and trained models are publicly available at https://github.com/MCG-NJU/MixFormer.
Recursion relations for orthogonal polynominals, arising in the study of the one-matrix model of two-dimensional gravity, are shown to be equvalent to the equations of the Toda-chain hierarchy supplemented by additional Virasoro constraints. This is the case without the double scaling limit. A discrete time variable to the matrix model is introduced. The discrete time dependent partition functions are given by $\tau$ functions which satisfy the discrete Toda molecule equation. Further the relations between the matrix model and the discrete time Toda theory are discussed.
We prove that a finite subset $A$ of the projective line $FP^1$ over a field $F$ of positive characteristic $p$ determines $\Omega(|A|^2)$ distinct cross-ratios, as long as $|A|<\sqrt{p}.$
Advancements in attention mechanisms have led to significant performance improvements in a variety of areas in machine learning due to its ability to enable the dynamic modeling of temporal sequences. A particular area in computer vision that is likely to benefit greatly from the incorporation of attention mechanisms in video action recognition. However, much of the current research's focus on attention mechanisms have been on spatial and temporal attention, which are unable to take advantage of the inherent motion found in videos. Motivated by this, we develop a new attention mechanism called Motion Aware Attention (M2A) that explicitly incorporates motion characteristics. More specifically, M2A extracts motion information between consecutive frames and utilizes attention to focus on the motion patterns found across frames to accurately recognize actions in videos. The proposed M2A mechanism is simple to implement and can be easily incorporated into any neural network backbone architecture. We show that incorporating motion mechanisms with attention mechanisms using the proposed M2A mechanism can lead to a +15% to +26% improvement in top-1 accuracy across different backbone architectures, with only a small increase in computational complexity. We further compared the performance of M2A with other state-of-the-art motion and attention mechanisms on the Something-Something V1 video action recognition benchmark. Experimental results showed that M2A can lead to further improvements when combined with other temporal mechanisms and that it outperforms other motion-only or attention-only mechanisms by as much as +60% in top-1 accuracy for specific classes in the benchmark.
We study electron transport through a semiconductor quantum ring with one input and two output terminals for an elastic scatterer present within one of the arms of the ring. We demonstrate that the scatterer not only introduces asymmetry in the transport probability to the two output leads but also reduces the visibility of the Aharonov-Bohm conductance oscillations. This reduction occurs in spite of the phase coherence of the elastic scattering and is due to interruption of the electron circulation around the ring by the potential defect. The results are in a qualitative agreement with a recent experiment by Strambini et al. [Phys. Rev. B {\bf 79}, 195443 (2009)]. We also indicate that the magnetic symmetry of the sum of conductance of both the output leads as obtained in the experiment can be understood as resulting from the invariance of backscattering to the input lead with respect to the magnetic field orientation.
In this paper, we count a dual set of Stirling permutations by the number of alternating runs. Properties of the generating functions, including recurrence relations, grammatical interpretations and convolution formulas are studied.
Multi-server queueing systems describe situations in which users require service from multiple parallel servers. Examples include check-in lines at airports, waiting rooms in hospitals, queues in contact centers, data buffers in wireless networks, and delayed service in cloud data centers. These are all situations with jobs (clients, patients, tasks) and servers (agents, beds, processors) that have large capacity levels, ranging from the order of tens (checkouts) to thousands (processors). This survey investigates how to design such systems to exploit resource pooling and economies-of-scale. In particular, we review the mathematics behind the Quality-and-Efficiency Driven (QED) regime, which lets the system operate close to full utilization, while the number of servers grows simultaneously large and delays remain manageable. Aimed at a broad audience, we describe in detail the mathematical concepts for the basic Markovian many-server system, and only provide sketches or references for more advanced settings related to e.g. load balancing, overdispersion, parameter uncertainty, general service requirements and queueing networks. While serving as a partial survey of a massive body of work, the tutorial is not aimed to be exhaustive.
We present radio and optical analysis of a sample of Low Luminosity Compact (LLC) objects, selected from FIRST survey and observed with MERLIN at L-band and C-band. The main criterion used for selection was luminosity of the objects and approximately one third of the CSS sources from the new sample have a value of radio luminosity comparable to FR\,Is.The analysis of a radio properties of LLC sources show they occupy the space in radio power versus linear size diagram below the main evolutionary path of radio objects. We suggest that many of them might be short-lived objects, and their radio emission may be disrupted several times before becoming FR\,IIs. The optical analysis of the LLC sources were made based on the available SDSS images and spectra. We have classified the sources as high and low excitation galaxies (HEG and LEG, respectively). The optical and radio properties of the LLC sample are in general consistent with brighter CSSs and large-scale radio sources. However, when LLC are added to the other samples, HEG and LEG seem to follow independent, parallel evolutionary tracks. LLC and luminous CSS behave like FR\,II sources, while FR\,I seem to belong to a different group of objects, concerning ionization mechanisms. Based on our results, we propose the independent, parallel evolutionary tracks for HEG and LEG sources, evolving from GPS - CSS - FR.
We employ the formalism of vanishing cycles and perverse sheaves to introduce and study the vanishing cohomology of complex projective hypersurfaces. As a consequence, we give upper bounds for the Betti numbers of projective hypersurfaces, generalizing those obtained by different methods by Dimca in the isolated singularities case, and by Siersma-Tib\u{a}r in the case of hypersurfaces with a $1$-dimensional singular locus. We also prove a supplement to the Lefschetz hyperplane theorem for hypersurfaces, which takes the dimension of the singular locus into account, and we use it to give a new proof of a result of Kato.
The goal of this paper is to present the way to define fermionic fields and their Lagrangians in terms of three orthogonal vector fields of norm 1 together with two real valued scalar fields. This paper is based on a toy model where there are no Grassmann variables.