Opportunity summary
Score4.0Public score shown from the verified overall while the stale axis breakdown refreshesThis canonical paper page includes Commercialization Proof and Related Resources.
ARXIV:2603.26154 · AI SECURITY · SUBMITTED 30 MAR · 21:58 UTC · FRESHNESS STALE
ARXIV:2603.26154AI SECURITYSUBMITTED 30 MAR · 21:58 UTCFRESHNESS STALEXiaofeng Li · Leyi Sheng · Zhen Sun · Zongmin Zhang · Jiaheng Wei · Xinlei He · arXiv
A benchmark for evaluating image protection methods in image-to-video generation to combat misuse.
Opportunity summary
Pain A benchmark for evaluating image protection methods in image-to-video generation to combat misuse.
Evidence 46 refs | 3 sources | 50% coverage
Blocker Evidence unverified
A benchmark for evaluating image protection methods in image-to-video generation to combat misuse. For instance, a single image can be exploited to generate a fake video, which can be used to attract attention and…
With the rapid advancement of image-to-video (I2V) generation models, their potential for misuse in creating malicious content has become a significant concern. For instance, a single image can be exploited to generate a fake…
ScienceToStartup currently rates this 4.0/10 on the public viability pass. Overall, IP-Bench establishes a systematic, reproducible, and extensible evaluation framework for image protection methods in I2V generation scenarios. Code availability is flagged in the…
AI Security moved forward this cycle; last verified April 2026. Public score 4.0/10. Production flags indicate code availability.
Continue into Read for claims, analysis, references, and neighboring papers.
mobile layout uses overflow-hidden min-w-0 break-wordsOpportunity summary
Score4.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
A benchmark for evaluating image protection methods in image-to-video generation to combat misuse.
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Paper Pack
10.48550/arXiv.2603.26154A benchmark for evaluating image protection methods in image-to-video generation to combat misuse.
Abstract
With the rapid advancement of image-to-video (I2V) generation models, their potential for misuse in creating malicious content has become a significant concern. For instance, a single image can be exploited to generate a fake video, which can be used to attract attention and gain benefits. This phenomenon is referred to as an I2V generation misuse. Existing image protection methods suffer from the absence of a unified benchmark, leading to an incomplete evaluation framework. Furthermore, these methods have not been systematically assessed in I2V generation scenarios and against preprocessing attacks, which complicates the evaluation of their effectiveness in real-world deployment scenarios.To address this challenge, we propose IP-Bench (Image Protection Bench), the first systematic benchmark designed to evaluate protection methods in I2V generation scenarios. This benchmark examines 6 representative protection methods and 5 state-of-the-art I2V models. Furthermore, our work systematically evaluates protection methods' robustness with two robustness attack strategies under practical scenarios and analyzes their cross-model & cross-modality transferability. Overall, IP-Bench establishes a systematic, reproducible, and extensible evaluation framework for image protection methods in I2V generation scenarios.
Source availability
PDF linkedThe paper record includes a public PDF URL.
Extraction status
Parse run pending anchorsA parse run id is attached, but no public source anchors are materialized yet.
Proof status
unverified46 refs; 3 sources; 50% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
Time to MVP
Commercial
Export
Preparing verified analysis
Dimensions overall score 4.0
PROBLEM
A benchmark for evaluating image protection methods in image-to-video generation to combat misuse. For instance, a single image can be exploited to generate a fake video, which can be used to attract attention and gain benefits.
METHOD
With the rapid advancement of image-to-video (I2V) generation models, their potential for misuse in creating malicious content has become a significant concern. For instance, a single image can be exploited to generate a fake video, which can be used to attract attention and gai...
RESULT
ScienceToStartup currently rates this 4.0/10 on the public viability pass. Overall, IP-Bench establishes a systematic, reproducible, and extensible evaluation framework for image protection methods in I2V generation scenarios. Code availability is flagged in the production recor...
WHY NOW
AI Security moved forward this cycle; last verified April 2026. Public score 4.0/10. Production flags indicate code availability.
I2VGuard [13] demonstrates notable robustness against pre- processing attacks, maintaining a degradation rate above 0.02 across most models.
This is a specific result presented in the paper with a quantitative measure.
partial
VGMShield [14] demonstrates strong performance on specific models such as W AN [22], achiev- ing a degradation rate of 0.036.
This is a specific result presented in the paper with a quantitative measure for a particular model.
partial
PhotoGuard [15] achieves a balanced performance, with a moderate PSNR of 31.77 and a degradation rate of 0.041 on Skyreel [23].
This is a specific result presented in the paper with quantitative measures for a particular model.
partial
Furthermore, no existing method transfers effectively across different archi- tectures
This is a stated limitation and a motivation for the benchmark, implying a finding from prior work.
partial
I2I-based approaches) across 5 widely used I2V models fea- turing distinct structures, such as DiT and U-Net [19, 20].
This is explicitly stated in the abstract and supported by the description of the I2V models used.
partial
To address this challenge, we propose IP-Bench (Image Protection Bench), the first systematic benchmark designed to evaluate protection methods in I2V generation scenarios.
This is explicitly stated in the abstract and reinforced throughout the introduction.
partial
This benchmark examines 6 representative protection methods and 5 state-of-the-art I2V models.
This is explicitly stated in the abstract and supported by the overview tables in the paper.
partial
Furthermore, our work systematically evaluates protection methods' robustness with two robustness attack strategies under practical scenarios and analyzes their cross-model & cross-modality transferability.
This is explicitly stated in the abstract and detailed in the methodology section.
partial
Paper-native neighborhood for concepts, methods, materials, markets, and competitors. Missing lanes stay labeled instead of disappearing behind commercialization gates.
Concepts
Methods
Materials
Markets
Competitors
A benchmark for evaluating image protection methods in image-to-video generation to combat misuse.
Segment
AI Security
Adoption evidence
No public code link in the paper record yet
Commercial read
4.0/10 public viability
Direct
Adjacent
Substitute
Unknown
No indexed public discussion is attached to 2603.26154 yet. That is a visibility signal, not a blank module: the monitor is watching the public channels below.
Hacker News
Not indexed yet
Not indexed yet
Bluesky
Not indexed yet
Preview the source document here, or use the hero PDF action for a new tab.
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.
Commercially relevant
Conflicting
Owned Distribution
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3/3 checks · 100%
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
Build brief missing until Build Passport data exists.
Source missing: Build Passport payload.
Experiment plan missing until prototype path is available.
No prototype path attached.
Validation checklist missing until required assets, cost, and regulatory flags are verified.
No checklist artifact is attached to the Build Passport payload.
Derived signals show verified:false until source-backed receipts exist.
Evidence coverage
OpportunityKernel evidence_receipt
46 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
Technical feasibility
partial
Current read
Runnable path is not fully verified.
Evidence
No Build Passport payload attached.
Gaps
Next test
Run minimal reproduction from the Build Passport prototype path.
Market urgency
partial
Current read
Research evidence exists; buyer urgency still needs source proof.
Evidence
46 references, 3 sources, 50% evidence coverage.
Gaps
Next test
Collect buyer interview, deployment evidence, or cited demand signal.
Buyer clarity
missing
Current read
No budget owner is verified for this paper.
Evidence
Build tab has no CRM, procurement, or operator source.
Gaps
Next test
Map target operator, economic buyer, and procurement trigger.
Defensibility
missing
Current read
Defensibility signals are missing.
Evidence
No defensibility receipt attached.
Gaps
Next test
Refresh defensibility bars with source receipts.
Integration burden
missing
Current read
No public implementation surface observed.
Evidence
No GitHub or Hugging Face payload attached.
Gaps
Next test
Write integration checklist from prototype path and target workflow.
Capital intensity
missing
Current read
No observed cost estimate is verified.
Evidence
Cost passport has no observed_usd value.
Gaps
Next test
Run cost passport or mark the cost field not applicable.
Regulatory load
missing
Current read
No regulatory classification is attached.
Evidence
Build Passport ledger does not include regulatory flags.
Gaps
Next test
Classify regulatory flags before commercialization planning.
No named scientific founder assigned.
Paper authors are not treated as operators without consent.
People
No named person assigned.
Gaps
Next verification path
Prototype owner missing.
Build Passport does not name an implementer.
People
No named person assigned.
Gaps
Next verification path
Operator workflow not sourced.
No buyer or workflow interview attached.
People
No named person assigned.
Gaps
Next verification path
No GTM owner verified.
No CRM or outreach source attached.
People
No named person assigned.
Gaps
Next verification path
Regulatory need unclassified.
No clinical or regulatory source attached.
People
No named person assigned.
Gaps
Next verification path
ARTIFACTS
No public artifacts yet.
DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
No verified watchtower monitor rows yet.
FORESIGHT
No prediction yet — minted on next Foresight batch.
OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
No verified OpportunityKernel changes since the last view.
COMPETITIVE LANDSCAPE UPDATES
No verified competitive landscape changes yet.
RELATED PAPER UPDATES
No verified related paper changes yet.
SIGNAL CANVAS HISTORY AND DELTAS
No Signal Canvas history deltas yet.
TIMELINE
Save this paper to start tracking momentum - commits, demos, and score changes appear here.
No tracked events yet.
Score trend will appear after multiple data points.
BUZZ
Buzz trend pending.