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Found 8 papers, 4 papers with code
TUMTraf V2X Cooperative Perception Dataset
We propose CoopDet3D, a cooperative multi-modal fusion model, and TUMTraf-V2X, a perception dataset, for the cooperative 3D object detection and tracking task.
Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations
The system strives to holistically capture and interpret the information content of CCTV footage spanning multiple frames to recognize instances of various violations of social distancing protocols, across time and space, as well as identification of group behaviors.
Hands Off: A Handshake Interaction Detection and Localization Model for COVID-19 Threat Control
The proposed model is the first dyadic interaction localizer in a multi-person setting, which enables it to be used in public spaces to identify handshake interactions and thereby identify and mitigate COVID-19 transmission.
A generalized forecasting solution to enable future insights of COVID-19 at sub-national level resolutions
In this study, a forecasting solution is proposed, to predict daily new cases of COVID-19 in regions small enough where containment measures could be locally implemented, by targeting three main shortcomings that exist in literature; the unreliability of existing data caused by inconsistent testing patterns in smaller regions, weak deploy-ability of forecasting models towards predicting cases in previously unseen regions, and model training biases caused by the imbalanced nature of data in COVID-19 epi-curves.
An Optical physics inspired CNN approach for intrinsic image decomposition
There is a lack of unsupervised learning approaches for decomposing an image into reflectance and shading using a single image.
A Retinex based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images
Low light image enhancement is an important challenge for the development of robust computer vision algorithms.
On Deep Learning for Radio Resource Management in A Non-stationary Radio Environment
This paper studies practical limitations of learning methods for resource management in non-stationary radio environment.
Non-contact Infant Sleep Apnea Detection
This paper presents a novel algorithm for the detection of sleep apnea with video processing.
