TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting
Paper • 2204.01018 • Published
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RepCount
Full-set metadata for lmms-eval task repcount.
Dataset Contents
This repository contains metadata/annotations only. Raw video files are not embedded in this repo.
QA Format
Each row is count-based QA for repetition counting:
video/video_id: media referencequestion: natural-language counting promptcount: integer ground-truth repetition countaction_type(optional): action category metadata
In lmms-eval, targets are read from count first (fallbacks: answer, number, gt_count, label), and scored by mae_norm and obo.
Raw Media Requirement
- Metadata source: https://github.com/sinhasaptarshi/EveryShotCounts (
datasets/repcount/*_with_fps.csv) - Raw video location: official RepCount downloads / YouTube-derived media (not embedded here)
- Expected local media root for evaluation:
$REPCOUNT_VIDEO_DIRor$HF_HOME/repcount
Attribution and Relationship
RepCount is introduced in TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting (CVPR 2022, arXiv:2204.01018). Countix is a separate dataset introduced in Counting Out Time (CVPR 2020, arXiv:2006.15418). RepCount and Countix are independent datasets from different research groups.
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