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ARXIV:2603.25163 · SPORTS SKILL LEARNING · SUBMITTED 31 MAR · 20:30 UTC · FRESHNESS STALE
ARXIV:2603.25163SPORTS SKILL LEARNINGSUBMITTED 31 MAR · 20:30 UTCFRESHNESS STALEKumar Ashutosh · Chi Hsuan Wu · Kristen Grauman · arXiv
A dataset and retrieval system for personalized sports skill improvement from instructional videos.
Opportunity summary
Pain A dataset and retrieval system for personalized sports skill improvement from instructional videos.
Evidence 0 refs | 0 sources | 33% coverage
Blocker Evidence unverified
A dataset and retrieval system for personalized sports skill improvement from instructional videos. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-wild video.
Current large-scale video datasets focus on general human activity, but lack depth of coverage on fine-grained activities needed to address physical skill learning. We introduce SportSkills, the first large-scale sports dataset geared towards physical…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Through a suite of experiments, we show that SportSkills unlocks the ability to understand fine-grained differences between physical actions. Code availability is flagged in…
Sports Skill Learning moved forward this cycle; last verified April 2026. Public score 7.0/10. Production flags indicate code availability.
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A dataset and retrieval system for personalized sports skill improvement from instructional videos.
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Paper Pack
10.48550/arXiv.2603.25163A dataset and retrieval system for personalized sports skill improvement from instructional videos.
Abstract
Current large-scale video datasets focus on general human activity, but lack depth of coverage on fine-grained activities needed to address physical skill learning. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-wild video. SportSkills has more than 360k instructional videos containing more than 630k visual demonstrations paired with instructional narrations explaining the know-how behind the actions from 55 varied sports. Through a suite of experiments, we show that SportSkills unlocks the ability to understand fine-grained differences between physical actions. Our representation achieves gains of up to 4x with the same model trained on traditional activity-centric datasets. Crucially, building on SportSkills, we introduce the first large-scale task formulation of mistake-conditioned instructional video retrieval, bridging representation learning and actionable feedback generation (e.g., "here's my execution of a skill; which video clip should I watch to improve it?"). Formal evaluations by professional coaches show our retrieval approach significantly advances the ability of video models to personalize visual instructions for a user query.
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Proof status
unverified0 refs; 0 sources; 33% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
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Dimensions overall score 7.0
PROBLEM
A dataset and retrieval system for personalized sports skill improvement from instructional videos. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-wild video.
METHOD
Current large-scale video datasets focus on general human activity, but lack depth of coverage on fine-grained activities needed to address physical skill learning. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-...
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Through a suite of experiments, we show that SportSkills unlocks the ability to understand fine-grained differences between physical actions. Code availability is flagged in the production record; the pub...
WHY NOW
Sports Skill Learning moved forward this cycle; last verified April 2026. Public score 7.0/10. Production flags indicate code availability.
Abstract-backed public claims while anchored extraction refreshes.
A dataset and retrieval system for personalized sports skill improvement from instructional videos. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-wild video.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Current large-scale video datasets focus on general human activity, but lack depth of coverage on fine-grained activities needed to address physical skill learning. We introduce SportSkills, the first large-scale sports dataset geared towards physical skill learning with in-the-wild video.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Through a suite of experiments, we show that SportSkills unlocks the ability to understand fine-grained differences between physical actions. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Sports Skill Learning moved forward this cycle; last verified April 2026. Public score 7.0/10. Production flags indicate code availability.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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A dataset and retrieval system for personalized sports skill improvement from instructional videos.
Segment
Sports Skill Learning
Adoption evidence
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Commercial read
7.0/10 public viability
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reason
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proof status
unverified
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confidence low
next verification path
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Evidence coverage
OpportunityKernel evidence_receipt
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stale
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passport absent
stale
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Artifact maturity
GitHub and Hugging Face maturity payloads
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stale
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Technical feasibility
partial
Current read
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Gaps
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Run minimal reproduction from the Build Passport prototype path.
Market urgency
missing
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Evidence
0 references, 0 sources, 33% evidence coverage.
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Buyer clarity
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No budget owner is verified for this paper.
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Integration burden
missing
Current read
No public implementation surface observed.
Evidence
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Write integration checklist from prototype path and target workflow.
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Classify regulatory flags before commercialization planning.
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ARTIFACTS
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DEFENSIBILITY
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