A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

PROBLEM

A unified generative framework using flow matching to perform text-driven motion editing and structural retargeting with a single model. We present a unifying perspective where both tasks are cast as instances of conditional transport…

METHOD

Full abstract

Text-driven motion editing and intra-structural retargeting, where source and target share topology but may differ in bone lengths, are traditionally handled by fragmented pipelines with incompatible inputs and representations: editing relies on specialized generative steering, while retargeting is deferred to geometric post-processing. We present a unifying perspective where both tasks are cast as instances of conditional transport within a single generative framework. By leveraging recent advances in flow matching, we demonstrate that editing and retargeting are fundamentally the same generative task, distinguished only by which conditioning signal, semantic or structural, is modulated during inference. We implement this vision via a rectified-flow motion model jointly conditioned on text prompts and target skeletal structures. Our architecture extends a DiT-style transformer with per-joint tokenization and explicit joint self-attention to strictly enforce kinematic dependencies, while a multi-condition classifier-free guidance strategy balances text adherence with skeletal conformity. Experiments on SnapMoGen and a multi-character Mixamo subset show that a single trained model supports text-to-motion generation, zero-shot editing, and zero-shot intra-structural retargeting. This unified approach simplifies deployment and improves structural consistency compared to task-specific baselines.

RESULT

ScienceToStartup currently rates this 8.0/10 on the public viability pass. By leveraging recent advances in flow matching, we demonstrate that editing and retargeting are fundamentally the same generative task, distinguished only by which conditioning…

WHY NOW

Motion Generation moved forward this cycle; last verified April 2026. Public score 8.0/10. Production flags indicate code availability.

Paper Pack

10.48550/arXiv.2604.13427

A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

A unified generative framework using flow matching to perform text-driven motion editing and structural retargeting with a single model.

Abstract

Source availability

PDF linked

The paper record includes a public PDF URL.

Extraction status

Parse run linked

A document parse run is attached to this paper.

Proof status

unverified

0 refs; 3 sources; 50% coverage.

What was readable

linkedon file20 anchorsderived fallbacknot indexednot indexed

Derived fallback: Estimated from adjacent evidence; not verified from source.

Viability

8.0

Time to MVP

MVP estimate missing

Commercial

code

Export

Preparing verified analysis

lens / agent

RESULT

PROBLEM

METHOD

WHY NOW

Motion Generation moved forward this cycle; last verified April 2026. Public score 8.0/10. Production flags indicate code availability.

Claim map

Abstract-backed public claims while anchored extraction refreshes.

Strong 0Mixed 0Weak 4

Evidencepartial
A unified generative framework using flow matching to perform text-driven motion editing and structural retargeting with a single model. We present a unifying perspective where both tasks are cast as instances of conditional transport within a single generative framework.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Text-driven motion editing and intra-structural retargeting, where source and target share topology but may differ in bone lengths, are traditionally handled by fragmented pipelines with incompatible inputs and representations: editing relies on specialized generative steering, while retargeting is deferred to geometric post-processing. We present a unifying perspective where both tasks are cast as instances of conditional transport within a single generative framework.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
ScienceToStartup currently rates this 8.0/10 on the public viability pass. By leveraging recent advances in flow matching, we demonstrate that editing and retargeting are fundamentally the same generative task, distinguished only by which conditioning signal, semantic or structural, is modulated during inference. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Motion Generation moved forward this cycle; last verified April 2026. Public score 8.0/10. Production flags indicate code availability.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial

PDF

Preview the source document here, or use the hero PDF action for a new tab.

REFERENCES

Reference metadata is not materialized in the public index yet. The source PDF remains the authority; cache refresh is optional.

CITED BY

No citing papers are indexed in the public S2S graph yet. This is an explicit zero-signal state, not a hidden lookup.

Foundation

Prior WorkControllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades

8.0

Prior WorkInterEdit: Navigating Text-Guided Multi-Human 3D Motion Editing

8.0

Extension

Builds On ThisUniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

4.0

Related Resources

Owned Distribution

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A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting | ScienceToStartup

2/3 checks · 67%

References 0 / 33+ references
Sources 3 / 22+ sources
Coverage 50% / 50%50%+ coverage

Build Passport

UNVERIFIED

Build Passport

Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap

status

missing

reason

passport_row_missing

proof status

unverified

cost/budget

No verified cost estimate

confidence low

next verification path

/api/v1/paper/2604.13427v1/paper-pack
/api/v1/paper/2604.13427v1/build-passport
Generate required assets: Dockerfile.minimal, RUN.sh, EXPECTED_OUTPUT.json, COST_PASSPORT.json

Build artifacts

Brief

missing

Build brief missing until Build Passport data exists.

Source missing: Build Passport payload.

Experiment plan

missing

Experiment plan missing until prototype path is available.

No prototype path attached.

Validation checklist

missing

Validation checklist missing until required assets, cost, and regulatory flags are verified.

No checklist artifact is attached to the Build Passport payload.

Signal Canvas

Derived signals show verified:false until source-backed receipts exist.

Open Signal Canvas

SignalSourceStrengthFreshnessOwner action

Evidence coverage

OpportunityKernel evidence_receipt

0 refs / 3 sources / 50% coverage

stale

Verify missing sources before using this as buyer proof. verified:false

Build readiness

BuildPassport EvidenceState

passport absent

stale

Run Proof Lab or inspect typed missing state. verified:false

Artifact maturity

GitHub and Hugging Face maturity payloads

No public artifact surface observed

stale

Open source artifacts or mark the gap as missing. verified:false

Viability breakdown

decision rows

DimensionCurrent readEvidenceGapsNext test

Technical feasibility

partial

Current read

Runnable path is not fully verified.

Evidence

No Build Passport payload attached.

Gaps

No verified reproduction transcript attached.

Next test

Run minimal reproduction from the Build Passport prototype path.

Market urgency

missing

Current read

Buyer urgency is not verified from source.

Talent buckets

no invented people

Scientific founder

Needed now

No named scientific founder assigned.

Paper authors are not treated as operators without consent.

People

No named person assigned.

Gaps

Founder commitment not verified.

Next verification path

Confirm founder/operator owner.

Translational engineer

Needed now

Prototype owner missing.

Build Passport does not name an implementer.

People

No named person assigned.

ARTIFACTS

No public artifacts yet.

DEFENSIBILITY

Defensibility and confidence evidence pending.

Paper Pack

10.48550/arXiv.2604.13427

A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

A unified generative framework using flow matching to perform text-driven motion editing and structural retargeting with a single model.

Abstract

Source availability

PDF linked

The paper record includes a public PDF URL.

Extraction status

Parse run linked

A document parse run is attached to this paper.

Proof status

unverified

0 refs; 3 sources; 50% coverage.

What was readable

linkedon file20 anchorsderived fallbacknot indexednot indexed

Derived fallback: Estimated from adjacent evidence; not verified from source.

Viability

8.0

Time to MVP

MVP estimate missing

Commercial

code

Export

Preparing verified analysis

lens / agent

RESULT

PROBLEM

METHOD

WHY NOW

Motion Generation moved forward this cycle; last verified April 2026. Public score 8.0/10. Production flags indicate code availability.

Claim map

Abstract-backed public claims while anchored extraction refreshes.

Strong 0Mixed 0Weak 4

Evidencepartial
A unified generative framework using flow matching to perform text-driven motion editing and structural retargeting with a single model. We present a unifying perspective where both tasks are cast as instances of conditional transport within a single generative framework.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Text-driven motion editing and intra-structural retargeting, where source and target share topology but may differ in bone lengths, are traditionally handled by fragmented pipelines with incompatible inputs and representations: editing relies on specialized generative steering, while retargeting is deferred to geometric post-processing. We present a unifying perspective where both tasks are cast as instances of conditional transport within a single generative framework.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
ScienceToStartup currently rates this 8.0/10 on the public viability pass. By leveraging recent advances in flow matching, we demonstrate that editing and retargeting are fundamentally the same generative task, distinguished only by which conditioning signal, semantic or structural, is modulated during inference. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Motion Generation moved forward this cycle; last verified April 2026. Public score 8.0/10. Production flags indicate code availability.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial

PDF

Preview the source document here, or use the hero PDF action for a new tab.

REFERENCES

Reference metadata is not materialized in the public index yet. The source PDF remains the authority; cache refresh is optional.

CITED BY

No citing papers are indexed in the public S2S graph yet. This is an explicit zero-signal state, not a hidden lookup.

Foundation

Prior WorkControllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades

8.0

Prior WorkInterEdit: Navigating Text-Guided Multi-Human 3D Motion Editing

8.0

Extension

Builds On ThisUniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

4.0

Related Resources

Owned Distribution

Subscribe to the weekly brief

Get the weekly shortlist of commercializable papers, benchmark movers, and proof receipts that matter for product execution.

Payload preview

Inspect payload

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Page Freshness

Canonical route, proof status, last verified, refs, sources, and coverage.

Page Freshness

Paper proof surface

Canonical route: /paper/a-unified-conditional-flow-for-motion-generation-editing-and-intra-structural-retargeting

stale

Proof freshness: stale
Proof status: unverified
Display score: 8/10
Last proof check: 2026-04-16
Score updated: 2026-04-16
Score fresh until: 2026-05-16
References: 0
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Endpoint list, payload shape, route context, and copyable handoff data.

Agent Handoff

A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

Canonical ID a-unified-conditional-flow-for-motion-generation-editing-and-intra-structural-retargeting | Route /paper/a-unified-conditional-flow-for-motion-generation-editing-and-intra-structural-retargeting

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/paper/a-unified-conditional-flow-for-motion-generation-editing-and-intra-structural-retargeting

MCP example

{
  "tool": "get_paper",
  "arguments": {
    "arxiv_id": "2604.13427"
  }
}

source_context

{
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Buildability Receipt

Verdict, compute envelope, blockers, signature state, and receipt links.

Paper proof page receipt window

Watch and verify: A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

/buildability/a-unified-conditional-flow-for-motion-generation-editing-and-intra-structural-retargeting

Watchwatch

Subject: A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Time to first demo

Insufficient data

No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.

Compute envelope

Structured compute envelope

Insufficient data

Source Proof anchors

Visual citations from the paper document graph.

Source proof

Visual citation anchors from the paper document graph.

20 anchors

proof blockPage 382%

This equation captures one of the core mathematical components of the system. x𝑡= xgen 𝑡 ; xret 𝑡 , xgen 𝑡 ∈R𝐷gen, xret 𝑡 ∈R𝐷ret. Generative Features (

Page and bbox are available; crop image is pending.

proof blockPage 482%

This equation captures one of the core mathematical components of the system. c = 𝜙(c𝜏+ c𝑠) ∈R𝐷ℎ H𝑡= reshape (WinX𝑡+ bin) ∈R𝐽×𝑑, 𝑑= 𝐷ℎ where 𝜙is a smal

Page and bbox are available; crop image is pending.

proof blockPage 482%

This equation captures one of the core mathematical components of the system. H𝑡= reshape (WinX𝑡+ bin) ∈R𝐽×𝑑, 𝑑= 𝐷ℎ where 𝜙is a small condition-merging

Page and bbox are available; crop image is pending.

JSON-LD twin

The application/ld+json payload rendered for agents.

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A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

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PDF

REFERENCES

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Scientific founder

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Timeline

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Scientific founder

Translational engineer

Domain operator

GTM lead

Regulatory/clinical advisor

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PDF

REFERENCES

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Constellation map

Competitive landscape

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Payload preview

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Paper proof surface

Agent Handoff

A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

Buildability Receipt

Watch and verify: A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting

Compute envelope

Source Proof anchors

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Hash state

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Blockers