computer-vision-1

Skills Assessment

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in skills-assessment-1

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Dataset

Best Model

Actions

Multimodal PISA

Libraries

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Use these libraries to find skills-assessment-1 models and implementations

Datasets

AQA-7

eSports Sensors Dataset

Multimodal PISA

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Most implemented papers

What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment

Paritosh Parmar, B. Morris•Sun Apr 07 2019

This paper proposes to learn spatio-temporal features that explain three related tasks - fine-grained action recognition, commentary generation, and estimating the AQA score, and shows that the MTL approach outperforms STL approach using two different kinds of architectures: C3D-AVG and MSCADC.

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Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset

Anton Smerdov, Bo Zhou, P. Lukowicz, A. Somov•Sun Nov 01 2020

It is demonstrated that stress and concentration levels for professional players are less correlated, meaning more independent playstyle, and that the absence of team communication does not affect the professional players as much as amateur ones.

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SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge

D. Stoyanov, Yuto Ishikawa, Yuriko Harai, Satoshi Kondo, Nicolás Ayobi, S. Bodenstedt, R. Sparks, Yang Liu, Jiayu Huo, Alejandro Granados, Maxence Boels, Dimitrios Psychogyios, Emanuele Colleoni, Beatrice van Amsterdam, Chih-Yang Li, Shu-Yu Huang, Yuchong Li, Fucang Jia, Baosheng Zou, Guotai Wang, Prokar Dasgupta, Sébastien Ourselin, Mengya Xu, An-Chi Wang, Yanan Wu, Long Bai, Hongliang Ren, Atsushi Yamada, Kazuyuki Hayashi, J. Simoens, Pieter DeBacker, Francesco Cisternino, Gabriele Furnari, Alex Mottrie, Federica Ferraguti, Satoshi Kasai, Kousuke Hirasawa, Soohee Kim, Seung Hyun Lee, Kyu Eun Lee, Hyoun-Joong Kong, Kui Fu, Chao Li, Shan An, Stefanie Krell, Alejandra Pérez, Santiago Rodríguez, Juanita Puentes, Pablo Arbeláez, O. Mohareri•Sat Dec 30 2023

This work releases the first multimodal, publicly available, in-vivo, dataset for surgical action recognition and semantic instrumentation segmentation, containing 50 suturing video segments of Robotic Assisted Radical Prostatectomy (RARP).

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Evaluating surgical skills from kinematic data using convolutional neural networks

Hassan Ismail Fawaz, G. Forestier, J. Weber, L. Idoumghar, Pierre-Alain Muller•Wed Jun 06 2018

A Convolutional Neural Network is designed to evaluate surgeon skills by extracting patterns in the surgeon motions performed in robotic surgery and this method achieved very competitive results with 100% accuracy on the suturing and needle passing tasks.

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Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario

Anton Smerdov, A. Somov, Anastasia Kiskun, Rostislav Shaniiazov, E. Burnaev•Sun Mar 31 2019

This work proposes a smart chair platform - an unobtrusive approach to the collection of data on the eSports athletes and data further processing with machine learning methods and demonstrates that the professional athletes can be identified by their behaviour on the chair while playing the game.

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eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart Chair

Anton Smerdov, A. Somov, E. Burnaev•Wed Jul 31 2019

The smart chair platform is proposed which is to collect data on the person's behavior on the chair using an integrated accelerometer, a gyroscope and a magnetometer to distinguish between the low-skilled and high-skilled players.

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Detecting Video Game Player Burnout With the Use of Sensor Data and Machine Learning

Anton Smerdov, Bo Zhou, P. Lukowicz, A. Somov, E. Burnaev•Sat Nov 28 2020

This article has trained machine learning models, including the transformer and gated recurrent unit, to predict whether the player wins the encounter taking place after some fixed time in the future, and investigated which physiological features affect the chance to win or lose the next in-game encounter.

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AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors

Evgeny Burnaev, Anton Smerdov, A. Somov•Sun Dec 06 2020

An Artificial Intelligence (AI) enabled solution for predicting the eSports player in-game performance using exclusively the data from sensors and has a number of promising applications for Pro eSports teams as well as a learning tool for amateur players.

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Temporally guided articulated hand pose tracking in surgical videos

Luowei Zhou, R. Dias, Jason J. Corso, Nathan Louis, S. Yule, Milisa Manojlovich, F. Pagani, D. Likosky•Mon Jan 11 2021

A novel hand pose estimation model, CondPose, is proposed, which improves detection and tracking accuracy by incorporating a pose prior into its prediction, and shows improvements over state-of-the-art methods which provide frame-wise independent predictions.

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Piano Skills Assessment

Paritosh Parmar, B. Morris, Jaiden Reddy•Tue Jan 12 2021

A first-of-its-kind dataset for multimodal skill assessment focusing on assessing piano player’s skill level is collected, questions are answered, work in automated evaluation of piano playing skills is initiated and baselines for future work are provided.

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Adding a benchmark result helps the community track progress.