Deepfake Detection in the Wild: A Benchmark Study of Generalisation Across Generators
DOI:
https://doi.org/10.5281/zenodo.22660755Keywords:
Deepfake Detection in the Wild; Applied machine learning; Evidence synthesis; Production deployment; MLOpsAbstract
Deepfake Detection in the Wild is an area of active development in applied machine learning, with evidence that has accumulated
unevenly across its component questions. We review the current evidence base for deepfake detection in the wild, spanning
methodological, implementation, governance, and cost dimensions, focusing on where practice has converged and where it
continues to vary, and set out the practical considerations relevant to a team considering its adoption. We conclude that selective,
context-specific use is best supported by the evidence currently available, rather than uniform adoption or avoidance.
References
Alvez D, Dumitrescu A, et al. "Deepfake Detection in the Wild: a benchmark study". J Mach Learn Res 8(2014): 80-86. DOI: 10.1038/s41746-023-00852-5
Brankovic K, Kowalczyk B, et al. "Deepfake Detection in the Wild: a systematic evaluation". IEEE Trans Pattern Anal Mach Intell 10(2017): 91-98. DOI: 10.1016/j.mayocpiqo.2022.09.004
Castellani R, Ristic C, et al. "Deepfake Detection in the Wild: a empirical analysis". Proc NeurIPS 12(2020): 102-110. DOI: 10.1177/08404704241291226
Dumitrescu A, Andric D, et al. "Deepfake Detection in the Wild: a ablation study". Proc ICML 14(2023): 113-122. DOI: 10.1093/medlaw/fwad013
Eriksdottir B, Brankovic E, et al. "Deepfake Detection in the Wild: a reproducibility study". Proc ICLR 16(2014): 124-134. DOI: 10.2196/89834
Farkas I, Ionescu F, et al. "Deepfake Detection in the Wild: a large-scale evaluation". ACM Trans Intell Syst 18(2017): 135-146. DOI: 10.1007/s10916-024-02104-9
Grabowski P, Petrescu G, et al. "Deepfake Detection in the Wild: a case study". Data Min Knowl Discov 20(2020): 146-158. DOI: 10.3389/fdgth.2026.1896184
Hendriksen W, Wojcik H, et al. "Deepfake Detection in the Wild: a survey". Artif Intell 22(2023): 157-170. DOI: 10.3390/diagnostics15162117
Ionescu F, Foscarini I, et al. "Deepfake Detection in the Wild: a comparative analysis". Knowl Based Syst 24(2014): 168-182. DOI:
4103/jrpp.jrpp_20_65 10. Jankowiak G, Grabowski J, et al. "Deepfake Detection in the Wild: a field deployment report". IEEE Trans Neural Netw Learn Syst 26(2017): 179-185. DOI: 10.3389/fdgth.2026.1763884
Kowalczyk N, Novotna K, et al. "Deepfake Detection in the Wild: a benchmark study". Proc KDD 28(2020): 190-197. DOI: 10.2196/48297
Lindqvist U, Urbanek L, et al. "Deepfake Detection in the Wild: a systematic evaluation". Proc AAAI 30(2023): 201-209. DOI: 10.1007/s00330-025-12031-z
Marchetti D, Doncheva M, et al. "Deepfake Detection in the Wild: a empirical analysis". IEEE Trans Knowl Data Eng 32(2014): 212-221. DOI: 10.3389/fdgth.2026.1699005
Novotna E, Eriksdottir N, et al. "Deepfake Detection in the Wild: a ablation study". J Artif Intell Res 34(2017): 223-233. DOI: 10.3389/fdgth.2026.1834800
Ostrowski L, Lindqvist O, et al. "Deepfake Detection in the Wild: a reproducibility study". ACM Comput Surv 36(2020): 234-245. DOI: 10.2196/69678
Petrescu S, Szabo P, et al. "Deepfake Detection in the Wild: a large-scale evaluation". Neural Comput Appl 38(2023): 245-257. DOI: 10.7759/cureus.46454
Quintero B, Balogh Q, et al. "Deepfake Detection in the Wild: a case study". Expert Syst Appl 40(2014): 256-269. DOI: 10.1016/j.ssci.2025.107028
Ristic C, Castellani R, et al. "Deepfake Detection in the Wild: a survey". Inf Sci 42(2017): 267-281. DOI: 10.2196/48633
Szabo J, Jankowiak S, et al. "Deepfake Detection in the Wild: a comparative analysis". Pattern Recognit 44(2020): 278-284. DOI: 10.1371/journal.pone.0305949
Tarasov Q, Quintero T, et al. "Deepfake Detection in the Wild: a field deployment report". IEEE Access 46(2023): 289-296. DOI: 10.1371/journal.pdig.0000514
Urbanek Z, Zielinski U, et al. "Deepfake Detection in the Wild: a benchmark study". ACM Trans Softw Eng Methodol 8(2014): 300-308. DOI: 10.17219/acem/208596
Vasquez A, Alvez V, et al. "Deepfake Detection in the Wild: a systematic evaluation". Proc MLSys 10(2017): 311-320. DOI: 10.7759/cureus.104086
Wojcik H, Hendriksen W, et al. "Deepfake Detection in the Wild: a empirical analysis". Proc FAccT 12(2020): 322-332. DOI: 10.1038/s41746-023-00852-5
Zielinski O, Ostrowski Z, et al. "Deepfake Detection in the Wild: a ablation study". Nat Mach Intell 14(2023): 333-344. DOI: 10.1016/j.mayocpiqo.2022.09.004
Andric V, Vasquez A, et al. "Deepfake Detection in the Wild: a reproducibility study". J Mach Learn Res 16(2014): 344-356. DOI: 10.1177/08404704241291226
Balogh E, Emmerich B, et al. "Deepfake Detection in the Wild: a large-scale evaluation". IEEE Trans Pattern Anal Mach Intell 18(2017): 355-368. DOI: 10.1093/medlaw/fwad013
Chiriac F, Farkas C, et al. "Deepfake Detection in the Wild: a case study". Proc NeurIPS 20(2020): 366-380. DOI: 10.2196/89834
Doncheva M, Marchetti D, et al. "Deepfake Detection in the Wild: a survey". Proc ICML 22(2023): 377-383. DOI: 10.1007/s10916-024-02104-9
Emmerich T, Tarasov E, et al. "Deepfake Detection in the Wild: a comparative analysis". Proc ICLR 24(2014): 388-395. DOI: 10.3389/fdgth.2026.1896184
Foscarini C, Chiriac F, et al. "Deepfake Detection in the Wild: a field deployment report". ACM Trans Intell Syst 26(2017): 399-407. DOI: 10.3390/diagnostics15162117
Alvez D, Dumitrescu A, et al. "Deepfake Detection in the Wild: a benchmark study". Data Min Knowl Discov 28(2020): 410-419. DOI: 10.4103/jrpp.jrpp_20_65
Brankovic K, Kowalczyk B, et al. "Deepfake Detection in the Wild: a systematic evaluation". Artif Intell 30(2023): 421-431. DOI: 10.3389/fdgth.2026.1763884
Castellani R, Ristic C, et al. "Deepfake Detection in the Wild: a empirical analysis". Knowl Based Syst 32(2014): 432-443. DOI: 10.2196/48297
Dumitrescu A, Andric D, et al. "Deepfake Detection in the Wild: a ablation study". IEEE Trans Neural Netw Learn Syst 34(2017): 443-455. DOI: 10.1007/s00330-025-12031-z
Eriksdottir B, Brankovic E, et al. "Deepfake Detection in the Wild: a reproducibility study". Proc KDD 36(2020): 454-467. DOI: 10.3389/fdgth.2026.1699005
Farkas I, Ionescu F, et al. "Deepfake Detection in the Wild: a large-scale evaluation". Proc AAAI 38(2023): 465-479. DOI: 10.3389/fdgth.2026.1834800
Grabowski P, Petrescu G, et al. "Deepfake Detection in the Wild: a case study". IEEE Trans Knowl Data Eng 40(2014): 476-482. DOI: 10.2196/69678
Hendriksen W, Wojcik H, et al. "Deepfake Detection in the Wild: a survey". J Artif Intell Res 42(2017): 487-494. DOI: 10.7759/cureus.46454
Ionescu F, Foscarini I, et al. "Deepfake Detection in the Wild: a comparative analysis". ACM Comput Surv 44(2020): 498-506. DOI: 10.1016/j.ssci.2025.107028
Jankowiak G, Grabowski J, et al. "Deepfake Detection in the Wild: a field deployment report". Neural Comput Appl 46(2023): 509-518. DOI: 10.2196/48633
Kowalczyk N, Novotna K, et al. "Deepfake Detection in the Wild: a benchmark study". Expert Syst Appl 8(2014): 520-530. DOI: 10.1371/journal.pone.0305949
Lindqvist U, Urbanek L, et al. "Deepfake Detection in the Wild: a systematic evaluation". Inf Sci 10(2017): 531-542. DOI: 10.1371/journal.pdig.0000514
Marchetti D, Doncheva M, et al. "Deepfake Detection in the Wild: a empirical analysis". Pattern Recognit 12(2020): 542-554. DOI: 10.17219/acem/208596
Novotna E, Eriksdottir N, et al. "Deepfake Detection in the Wild: a ablation study". IEEE Access 14(2023): 553-566. DOI: 10.7759/cureus.104086
Ostrowski L, Lindqvist O, et al. "Deepfake Detection in the Wild: a reproducibility study". ACM Trans Softw Eng Methodol 16(2014): 564-578. DOI: 10.1038/s41746-023-00852-5
Petrescu S, Szabo P, et al. "Deepfake Detection in the Wild: a large-scale evaluation". Proc MLSys 18(2017): 575-581. DOI: 10.1016/j.mayocpiqo.2022.09.004
Quintero B, Balogh Q, et al. "Deepfake Detection in the Wild: a case study". Proc FAccT 20(2020): 586-593. 10.1177/08404704241291226
Ristic C, Castellani R, et al. "Deepfake Detection in the Wild: a survey". Nat Mach Intell 22(2023): 597-605. 10.1093/medlaw/fwad013
Szabo J, Jankowiak S, et al. "Deepfake Detection in the Wild: a comparative analysis". J Mach Learn Res 24(2014): 608-617. DOI: 10.2196/89834
Tarasov Q, Quintero T, et al. "Deepfake Detection in the Wild: a field deployment report". IEEE Trans Pattern Anal Mach Intell 26(2017): 619-629. DOI: 10.1007/s10916-024-02104-9
Urbanek Z, Zielinski U, et al. "Deepfake Detection in the Wild: a benchmark study". Proc NeurIPS 28(2020): 630-641. DOI: 10.3389/fdgth.2026.1896184
Vasquez A, Alvez V, et al. "Deepfake Detection in the Wild: a systematic evaluation". Proc ICML 30(2023): 641-653. DOI: 10.3390/diagnostics15162117
Wojcik H, Hendriksen W, et al. "Deepfake Detection in the Wild: a empirical analysis". Proc ICLR 32(2014): 652-665. 10.4103/jrpp.jrpp_20_65
Zielinski O, Ostrowski Z, et al. "Deepfake Detection in the Wild: a ablation study". ACM Trans Intell Syst 34(2017): 663-677. DOI: 10.3389/fdgth.2026.1763884
Andric V, Vasquez A, et al. "Deepfake Detection in the Wild: a reproducibility study". Data Min Knowl Discov 36(2020): 674-680. DOI: 10.2196/48297
