robert80203/EgoPER_official
The official implementation of Error Detection in Egocentric Procedural Task Videos
This project helps researchers and scientists automatically detect errors in first-person procedural task videos, like someone assembling furniture or performing a lab experiment. It takes in raw video footage and detailed annotations of the task steps and objects, and outputs identified errors in the procedure. This is useful for anyone studying human performance, training, or task analysis in fields like human-computer interaction or cognitive science.
No commits in the last 6 months.
Use this if you are analyzing video recordings of people performing a series of steps and need to automatically flag when a mistake or deviation from the correct procedure occurs.
Not ideal if your videos are not first-person (egocentric) or if you lack detailed annotations describing each step and object involved in the task.
Stars
22
Forks
5
Language
Python
License
—
Category
Last pushed
Sep 20, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/robert80203/EgoPER_official"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
patrikhuber/eos
A lightweight 3D Morphable Face Model library in modern C++
Uason-Chen/CTR-GCN
[ICCV2021] Official code for "Channel-wise Topology Refinement Graph Convolution for...
PeterL1n/BackgroundMattingV2
Real-Time High-Resolution Background Matting
PeterL1n/RobustVideoMatting
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Zielon/MICA
MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]