1 code implementation • 10 Mar 2024 • Paweł A. Pierzchlewicz, Caio da Silva, R. James Cotton, Fabian H. Sinz
In this study we focus on the new task of multi-hypothesis motion estimation.
no code implementations • 27 Feb 2024 • R. James Cotton
Recent developments have created differentiable physics simulators designed for machine learning pipelines that can be accelerated on a GPU.
no code implementations • 20 Feb 2024 • Nikolaos Smyrnakis, Tasos Karakostas, R. James Cotton
Gait analysis from videos obtained from a smartphone would open up many clinical opportunities for detecting and quantifying gait impairments.
no code implementations • 29 Dec 2023 • Kandan Ramakrishnan, R. James Cotton, Xaq Pitkow, Andreas S. Tolias
We systematically test the model under a number of different OOD generalization scenarios such as extrapolation to new object attributes, introducing new conjunctions or new attributes.
no code implementations • 30 Oct 2023 • R. James Cotton, Colleen Peyton
This work paves the way for advanced movement analysis tools that can be applied to diverse clinical populations, with a particular emphasis on early detection in infants.
no code implementations • 30 Jul 2023 • R. James Cotton, J. D. Peiffer, Kunal Shah, Allison DeLillo, Anthony Cimorelli, Shawana Anarwala, Kayan Abdou, Tasos Karakostas
We find that contrastive learning on unannotated gait data learns a representation that captures clinically meaningful information.
no code implementations • 19 Mar 2023 • R. James Cotton, Allison DeLillo, Anthony Cimorelli, Kunal Shah, J. D. Peiffer, Shawana Anarwala, Kayan Abdou, Tasos Karakostas
Markerless motion capture using computer vision and human pose estimation (HPE) has the potential to expand access to precise movement analysis.
no code implementations • 4 Mar 2023 • R. James Cotton, Anthony Cimorelli, Kunal Shah, Shawana Anarwala, Scott Uhlrich, Tasos Karakostas
Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis.
1 code implementation • 20 Oct 2022 • Paweł A. Pierzchlewicz, R. James Cotton, Mohammad Bashiri, Fabian H. Sinz
We evaluate cGNF on the Human~3. 6M dataset and show that cGNF provides a well-calibrated distribution estimate while being close to state-of-the-art in terms of overall minMPJPE.
Density Estimation Multi-Hypotheses 3D Human Pose Estimation
no code implementations • 17 Mar 2022 • R. James Cotton, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel, Tasos Karakostas
Human pose estimation from monocular video is a rapidly advancing field that offers great promise to human movement science and rehabilitation.
1 code implementation • 16 Mar 2022 • R. James Cotton
We also highlight limitations of these algorithms when applied to clinical populations in a rehabilitation setting.
no code implementations • 29 Sep 2021 • R. James Cotton, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel
Using more than 9000 monocular video from an instrumented gait analysis lab, we evaluated the performance of existing algorithms for measuring kinematics.
1 code implementation • 22 Oct 2020 • R. James Cotton, Fabian H. Sinz, Andreas S. Tolias
We overcome this limitation by formulating the problem as $K$-shot prediction to directly infer a neuron's tuning function from a small set of stimulus-response pairs using a Neural Process.