Repetitive Action Counting
3개 벤치마크 · 논문 14편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
A Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos
Counting Out Time: Class Agnostic Video Repetition Counting in the Wild
Rethinking temporal self-similarity for repetitive action counting
Every Shot Counts: Using Exemplars for Repetition Counting in Videos
PoseRAC: Pose Saliency Transformer for Repetitive Action Counting
Papers
CountLLM: Towards Generalizable Repetitive Action Counting via Large Language Model
Repetitive action counting, which aims to count periodic movements in a video, is valuable for video analysis applications such as fitness monitoring. However, existing methods largely rely on regression networks with li…
Language ModelingLanguage ModellingLarge Language ModelRepetitive Action CountingLocalization-Aware Multi-Scale Representation Learning for Repetitive Action Counting
Repetitive action counting (RAC) aims to estimate the number of class-agnostic action occurrences in a video without exemplars. Most current RAC methods rely on a raw frame-to-frame similarity representation for period p…
Repetitive Action CountingRepresentation LearningRepetitive Action Counting with Hybrid Temporal Relation Modeling
Repetitive Action Counting (RAC) aims to count the number of repetitive actions occurring in videos. In the real world, repetitive actions have great diversity and bring numerous challenges (e.g., viewpoint changes, non-…
RelationRepetitive Action CountingA Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos
We discuss some consistent issues on how RepNet has been evaluated in various papers. As a way to mitigate these issues, we report RepNet performance results on different datasets, and release evaluation code and the Rep…
Repetitive Action CountingMultiCounter: Multiple Action Agnostic Repetition Counting in Untrimmed Videos
Multi-instance Repetitive Action Counting (MRAC) aims to estimate the number of repetitive actions performed by multiple instances in untrimmed videos, commonly found in human-centric domains like sports and exercise. In…
GPURepetitive Action CountingGMFL-Net: A Global Multi-geometric Feature Learning Network for Repetitive Action Counting
With the continuous development of deep learning, the field of repetitive action counting is gradually gaining notice from many researchers. Extraction of pose keypoints using human pose estimation networks is proven to …
Pose EstimationRepetitive Action CountingSemantic SimilaritySemantic Textual Similarity