Learning Consistent Temporal Grounding between Related Tasks in Sports Coaching
Learning Consistent Temporal Grounding between Related Tasks in Sports Coaching explores Improve temporal grounding in video analysis for sports coaching by enforcing self-consistency between related tasks, outperforming existing methods without additional annotations.. Commercial viability score: 4/10 in Video Understanding.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Prior WorkTemporal Gains, Spatial Costs: Revisiting Video Fine-Tuning in Multimodal Large Language ModelsViability: 4.0
- Higher ViabilityVisionCoach: Reinforcing Grounded Video Reasoning via Visual-Perception PromptingViability: 7.0
- Higher ViabilityReinforcing Consistency in Video MLLMs with Structured RewardsViability: 7.0
- Higher ViabilityLearning Transferable Temporal Primitives for Video Reasoning via Synthetic VideosViability: 8.0
- Higher ViabilityGroundVTS: Visual Token Sampling in Multimodal Large Language Models for Video Temporal Grounding