Learning to score the figure skating sports videos

2018/02/08 by Chengming Xu, Xu, Chengming, Yanwei Fu +9 · 10 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimedia (cs.MM) #cs.CV #cs.MM

paper · pdf · doi:10.48550/arxiv.1802.02774

arxiv created 2018/07/28 · arxiv updated 2018/07/31

Abstract

This paper targets at learning to score the figure skating sports videos. To address this task, we propose a deep architecture that includes two complementary components, i.e., Self-Attentive LSTM and Multi-scale Convolutional Skip LSTM. These two components can efficiently learn the local and global sequential information in each video. Furthermore, we present a large-scale figure skating sports video dataset -- FisV dataset. This dataset includes 500 figure skating videos with the average length of 2 minutes and 50 seconds. Each video is annotated by two scores of nine different referees, i.e., Total Element Score(TES) and Total Program Component Score (PCS). Our proposed model is validated on FisV and MIT-skate datasets. The experimental results show the effectiveness of our models in learning to score the figure skating videos.

Cited by

• SkillSight: Efficient First-Person Skill Assessment with Gaze
• MCMoE: Completing Missing Modalities with Mixture of Experts for Incomplete Multimodal Action Quality Assessment
• FineSkiing: A Fine-grained Benchmark for Skiing Action Quality Assessment
• Learning Long-Range Action Representation by Two-Stream Mamba Pyramid Network for Figure Skating Assessment
• VIFSS: View-Invariant and Figure Skating-Specific Pose Representation Learning for Temporal Action Segmentation
• Attention-Driven Multimodal Alignment for Long-term Action Quality Assessment
• Predicting Soccer Penalty Kick Direction Using Human Action Recognition
• Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
• PHI: Bridging Domain Shift in Long-Term Action Quality Assessment via Progressive Hierarchical Instruction
• FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understanding

Related

• Skating-Mixer: Long-Term Sport Audio-Visual Modeling with MLPs
• YourSkatingCoach: A Figure Skating Video Benchmark for Fine-Grained Element Analysis
• Learning Long-Range Action Representation by Two-Stream Mamba Pyramid Network for Figure Skating Assessment
• Learning To Score Olympic Events
• FSD-10: A Dataset for Competitive Sports Content Analysis