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Found 11 papers, 11 papers with code
NOISe: Nuclei-Aware Osteoclast Instance Segmentation for Mouse-to-Human Domain Transfer
In the last few years, a handful of machine learning approaches for osteoclast image analysis have been developed, but none have addressed the full instance segmentation task required to produce the same output as that of the human expert led process.
WB LUTs: Contrastive Learning for White Balancing Lookup Tables
Automatic white balancing (AWB), one of the first steps in an integrated signal processing (ISP) pipeline, aims to correct the color cast induced by the scene illuminant.
Subtle Signals: Video-based Detection of Infant Non-nutritive Sucking as a Neurodevelopmental Cue
Non-nutritive sucking (NNS), which refers to the act of sucking on a pacifier, finger, or similar object without nutrient intake, plays a crucial role in assessing healthy early development.
Automatic Infant Respiration Estimation from Video: A Deep Flow-based Algorithm and a Novel Public Benchmark
Respiration is a critical vital sign for infants, and continuous respiratory monitoring is particularly important for newborns.
A Video-based End-to-end Pipeline for Non-nutritive Sucking Action Recognition and Segmentation in Young Infants
Tested on our second, independent, and public NNS in-the-wild dataset, NNS recognition classification reaches 92. 3\% accuracy, and NNS segmentation achieves 90. 8\% precision and 84. 2\% recall.
Automatic Assessment of Infant Face and Upper-Body Symmetry as Early Signs of Torticollis
We apply computer vision pose estimation techniques developed expressly for the data-scarce infant domain to the study of torticollis, a common condition in infants for which early identification and treatment is critical.
Computer Vision to the Rescue: Infant Postural Symmetry Estimation from Incongruent Annotations
Bilateral postural symmetry plays a key role as a potential risk marker for autism spectrum disorder (ASD) and as a symptom of congenital muscular torticollis (CMT) in infants, but current methods of assessing symmetry require laborious clinical expert assessments.
InfAnFace: Bridging the infant-adult domain gap in facial landmark estimation in the wild
We lay the groundwork for research in the algorithmic comprehension of infant faces, in anticipation of applications from healthcare to psychology, especially in the early prediction of developmental disorders.
Hindsight Foresight Relabeling for Meta-Reinforcement Learning
Meta-reinforcement learning (meta-RL) algorithms allow for agents to learn new behaviors from small amounts of experience, mitigating the sample inefficiency problem in RL.
Heuristic Weakly Supervised 3D Human Pose Estimation
However, recent models depend on supervised training with 3D pose ground truth data or known pose priors for their target domains.
Ranked #26 on
Weakly-supervised 3D Human Pose Estimation
on Human3.6M
Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch
In this paper, we propose a new framework for transfer learning where the teacher and the student can have arbitrarily different state- and action-spaces.
