Papers Unity
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M3Act: Learning from Synthetic Human Group Activities
The study of complex human interactions and group activities has become a focal point in human-centric computer vision. However, progress in related tasks is often hindered by the challenges of obtaining large-scale labe…
Activity RecognitionGroup Activity RecognitionInstance SegmentationPerson Recognition+3Inference in Predictive Quantile Regressions
This paper studies inference in predictive quantile regressions when the predictive regressor has a near-unit root. We derive asymptotic distributions for the quantile regression estimator and its heteroskedasticity and …
quantile regressionregressionUnitySteady-state analysis of networked epidemic models
Compartmental epidemic models with dynamics that evolve over a graph network have gained considerable importance in recent years but analysis of these models is in general difficult due to their complexity. In this paper…
UnityEnhancing biodiversity through intraspecific suppression in large ecosystems
The competitive exclusion principle (CEP) is a fundamental concept in the niche theory, which posits that the number of available resources constrains the coexistence of species. While the CEP offers an intuitive explana…
DiversityUnityXAI in Computational Linguistics: Understanding Political Leanings in the Slovenian Parliament
The work covers the development and explainability of machine learning models for predicting political leanings through parliamentary transcriptions. We concentrate on the Slovenian parliament and the heated debate on th…
Explainable Artificial Intelligence (XAI)UnityPersistent Homology Meets Object Unity: Object Recognition in Clutter
Recognition of occluded objects in unseen and unstructured indoor environments is a challenging problem for mobile robots. To address this challenge, we propose a new descriptor, TOPS, for point clouds generated from dep…
ObjectObject RecognitionUnityDevelopment of a Realistic Crowd Simulation Environment for Fine-grained Validation of People Tracking Methods
Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools …
Multiple People TrackingUnityCrowdSim2: an Open Synthetic Benchmark for Object Detectors
Data scarcity has become one of the main obstacles to developing supervised models based on Artificial Intelligence in Computer Vision. Indeed, Deep Learning-based models systematically struggle when applied in new scena…
ObjectObject DetectionUnityvehicle detectionExact Set-valued Estimation using Constrained Convex Generators for uncertain Linear Systems
Set-valued state estimation when in the presence of uncertainties in the model have been addressed in the literature essentially following three main approaches: i) interval arithmetic of the uncertain dynamics with the …
Autonomous VehiclesState EstimationUnityMathematical Model for Transmission Dynamics of Tuberculosis in Burundi
Tuberculosis (TB) is among the main public health challenges in Burundi. The literature lacks mathematical models for key parameter estimates of TB transmission dynamics in Burundi. In this paper, the supectible-exposed-…
SensitivityUnityA Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers
Interpretability is highly desired for deep neural network-based classifiers, especially when addressing high-stake decisions in medical imaging. Commonly used post-hoc interpretability methods have the limitation that t…
Binary ClassificationDecoderImage ClassificationMedical Image Classification+1Artificial Intelligence: 70 Years Down the Road
Artificial intelligence (AI) has a history of nearly a century from its inception to the present day. We have summarized the development trends and discovered universal rules, including both success and failure. We have …
UnityVirtual Guidance as a Mid-level Representation for Navigation with Augmented Reality
In the context of autonomous navigation, effectively conveying abstract navigational cues to agents in dynamic environments presents significant challenges, particularly when navigation information is derived from divers…
Autonomous NavigationUnityCAMEL: Curvature-Augmented Manifold Embedding and Learning
A novel method, named Curvature-Augmented Manifold Embedding and Learning (CAMEL), is proposed for high dimensional data classification, dimension reduction, and visualization. CAMEL utilizes a topology metric defined on…
Computational EfficiencyDimensionality ReductionUnitySUPS: A Simulated Underground Parking Scenario Dataset for Autonomous Driving
Automatic underground parking has attracted considerable attention as the scope of autonomous driving expands. The auto-vehicle is supposed to obtain the environmental information, track its location, and build a reliabl…
3D ReconstructionAutonomous DrivingDepth EstimationSemantic Segmentation+2Learning stiff chemical kinetics using extended deep neural operators
We utilize neural operators to learn the solution propagator for the challenging chemical kinetics equation. Specifically, we apply the deep operator network (DeepONet) along with its extensions, such as the autoencoder-…
UnityVersatile User Identification in Extended Reality using Pretrained Similarity-Learning
Various machine learning approaches have proven to be useful for user verification and identification based on motion data in eXtended Reality (XR). However, their real-world application still faces significant challenge…
Metric LearningUnityUser IdentificationWindowed Fourier Analysis for Signal Processing on Graph Bundles
We consider the task of representing signals supported on graph bundles, which are generalizations of product graphs that allow for "twists" in the product structure. Leveraging the localized product structure of a graph…
UnityStructural Break Detection in Quantile Predictive Regression Models with Persistent Covariates
We propose an econometric environment for structural break detection in nonstationary quantile predictive regressions. We establish the limit distributions for a class of Wald and fluctuation type statistics based on bot…
ManagementregressionTime SeriesTime Series Analysis+1Neurorehab: An Interface for Rehabilitation
About 15% of the world population is affected by a disability in some form, amongst whom only 31% perform the recommended exercises without intervention. We are working on developing a motivating and effective way to enc…
Brain Computer InterfaceGame DesignUnity