Towards More Accurate Fake Detection on Images Generated from Advanced Generative and Neural Rendering Models Article Swipe

PDF

Cheng‐Di Dong , B. V. K. Vijaya Kumar , Zhenyu Zhou , Ajay Kumar ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2411.08642

The remarkable progress in neural-network-driven visual data generation, especially with neural rendering techniques like Neural Radiance Fields and 3D Gaussian splatting, offers a powerful alternative to GANs and diffusion models. These methods can produce high-fidelity images and lifelike avatars, highlighting the need for robust detection methods. In response, an unsupervised training technique is proposed that enables the model to extract comprehensive features from the Fourier spectrum magnitude, thereby overcoming the challenges of reconstructing the spectrum due to its centrosymmetric properties. By leveraging the spectral domain and dynamically combining it with spatial domain information, we create a robust multimodal detector that demonstrates superior generalization capabilities in identifying challenging synthetic images generated by the latest image synthesis techniques. To address the absence of a 3D neural rendering-based fake image database, we develop a comprehensive database that includes images generated by diverse neural rendering techniques, providing a robust foundation for evaluating and advancing detection methods.

Related Topics

Rendering (Computer Graphics)

Generative Grammar

Artificial Intelligence

Computer Science

Computer Vision

Concepts

Rendering (computer graphics) Generative grammar Artificial intelligence Computer science Generative model Computer vision Pattern recognition (psychology)

Metadata

Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2411.08642
PDF: https://arxiv.org/pdf/2411.08642
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4404407873

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4404407873

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.48550/arxiv.2411.08642

Digital Object Identifier
Title: Towards More Accurate Fake Detection on Images Generated from Advanced Generative and Neural Rendering Models

Work title
Type: preprint

OpenAlex work type
Language: en

Primary language
Publication year: 2024

Year of publication
Publication date: 2024-11-13

Full publication date if available
Authors: Cheng‐Di Dong, B. V. K. Vijaya Kumar, Zhenyu Zhou, Ajay Kumar

List of authors in order
Landing page: https://arxiv.org/abs/2411.08642

Publisher landing page
PDF URL: https://arxiv.org/pdf/2411.08642

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: green

Open access status per OpenAlex
OA URL: https://arxiv.org/pdf/2411.08642

Direct OA link when available
Concepts: Rendering (computer graphics), Generative grammar, Artificial intelligence, Computer science, Generative model, Computer vision, Pattern recognition (psychology)

Top concepts (fields/topics) attached by OpenAlex
Cited by: 0

Total citation count in OpenAlex
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4404407873
doi	https://doi.org/10.48550/arxiv.2411.08642
ids.doi	https://doi.org/10.48550/arxiv.2411.08642
ids.openalex	https://openalex.org/W4404407873
fwci
type	preprint
title	Towards More Accurate Fake Detection on Images Generated from Advanced Generative and Neural Rendering Models
biblio.issue
biblio.volume
biblio.last_page
biblio.first_page
topics[0].id	https://openalex.org/T12357
topics[0].field.id	https://openalex.org/fields/17
topics[0].field.display_name	Computer Science
topics[0].score	0.9994000196456909
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/1707
topics[0].subfield.display_name	Computer Vision and Pattern Recognition
topics[0].display_name	Digital Media Forensic Detection
topics[1].id	https://openalex.org/T10775
topics[1].field.id	https://openalex.org/fields/17
topics[1].field.display_name	Computer Science
topics[1].score	0.9858999848365784
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/1707
topics[1].subfield.display_name	Computer Vision and Pattern Recognition
topics[1].display_name	Generative Adversarial Networks and Image Synthesis
topics[2].id	https://openalex.org/T10388
topics[2].field.id	https://openalex.org/fields/17
topics[2].field.display_name	Computer Science
topics[2].score	0.9404000043869019
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/1707
topics[2].subfield.display_name	Computer Vision and Pattern Recognition
topics[2].display_name	Advanced Steganography and Watermarking Techniques
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C205711294
concepts[0].level	2
concepts[0].score	0.7693322896957397
concepts[0].wikidata	https://www.wikidata.org/wiki/Q176953
concepts[0].display_name	Rendering (computer graphics)
concepts[1].id	https://openalex.org/C39890363
concepts[1].level	2
concepts[1].score	0.642870306968689
concepts[1].wikidata	https://www.wikidata.org/wiki/Q36108
concepts[1].display_name	Generative grammar
concepts[2].id	https://openalex.org/C154945302
concepts[2].level	1
concepts[2].score	0.5884318947792053
concepts[2].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[2].display_name	Artificial intelligence
concepts[3].id	https://openalex.org/C41008148
concepts[3].level	0
concepts[3].score	0.5845799446105957
concepts[3].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[3].display_name	Computer science
concepts[4].id	https://openalex.org/C167966045
concepts[4].level	3
concepts[4].score	0.4855015277862549
concepts[4].wikidata	https://www.wikidata.org/wiki/Q5532625
concepts[4].display_name	Generative model
concepts[5].id	https://openalex.org/C31972630
concepts[5].level	1
concepts[5].score	0.444438099861145
concepts[5].wikidata	https://www.wikidata.org/wiki/Q844240
concepts[5].display_name	Computer vision
concepts[6].id	https://openalex.org/C153180895
concepts[6].level	2
concepts[6].score	0.34930771589279175
concepts[6].wikidata	https://www.wikidata.org/wiki/Q7148389
concepts[6].display_name	Pattern recognition (psychology)
keywords[0].id	https://openalex.org/keywords/rendering
keywords[0].score	0.7693322896957397
keywords[0].display_name	Rendering (computer graphics)
keywords[1].id	https://openalex.org/keywords/generative-grammar
keywords[1].score	0.642870306968689
keywords[1].display_name	Generative grammar
keywords[2].id	https://openalex.org/keywords/artificial-intelligence
keywords[2].score	0.5884318947792053
keywords[2].display_name	Artificial intelligence
keywords[3].id	https://openalex.org/keywords/computer-science
keywords[3].score	0.5845799446105957
keywords[3].display_name	Computer science
keywords[4].id	https://openalex.org/keywords/generative-model
keywords[4].score	0.4855015277862549
keywords[4].display_name	Generative model
keywords[5].id	https://openalex.org/keywords/computer-vision
keywords[5].score	0.444438099861145
keywords[5].display_name	Computer vision
keywords[6].id	https://openalex.org/keywords/pattern-recognition
keywords[6].score	0.34930771589279175
keywords[6].display_name	Pattern recognition (psychology)
language	en
locations[0].id	pmh:oai:arXiv.org:2411.08642
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S4306400194
locations[0].source.issn
locations[0].source.type	repository
locations[0].source.is_oa	True
locations[0].source.issn_l
locations[0].source.is_core	False
locations[0].source.is_in_doaj	False
locations[0].source.display_name	arXiv (Cornell University)
locations[0].source.host_organization	https://openalex.org/I205783295
locations[0].source.host_organization_name	Cornell University
locations[0].source.host_organization_lineage	https://openalex.org/I205783295
locations[0].license
locations[0].pdf_url	https://arxiv.org/pdf/2411.08642
locations[0].version	submittedVersion
locations[0].raw_type
locations[0].license_id
locations[0].is_accepted	False
locations[0].is_published	False
locations[0].raw_source_name
locations[0].landing_page_url	http://arxiv.org/abs/2411.08642
locations[1].id	doi:10.48550/arxiv.2411.08642
locations[1].is_oa	True
locations[1].source.id	https://openalex.org/S4306400194
locations[1].source.issn
locations[1].source.type	repository
locations[1].source.is_oa	True
locations[1].source.issn_l
locations[1].source.is_core	False
locations[1].source.is_in_doaj	False
locations[1].source.display_name	arXiv (Cornell University)
locations[1].source.host_organization	https://openalex.org/I205783295
locations[1].source.host_organization_name	Cornell University
locations[1].source.host_organization_lineage	https://openalex.org/I205783295
locations[1].license
locations[1].pdf_url
locations[1].version
locations[1].raw_type	article
locations[1].license_id
locations[1].is_accepted	False
locations[1].is_published
locations[1].raw_source_name
locations[1].landing_page_url	https://doi.org/10.48550/arxiv.2411.08642
indexed_in	arxiv, datacite
authorships[0].author.id	https://openalex.org/A5015918478
authorships[0].author.orcid	https://orcid.org/0000-0002-4758-3739
authorships[0].author.display_name	Cheng‐Di Dong
authorships[0].author_position	first
authorships[0].raw_author_name	Dong, Chengdong
authorships[0].is_corresponding	False
authorships[1].author.id	https://openalex.org/A5055345322
authorships[1].author.orcid	https://orcid.org/0000-0001-7126-6381
authorships[1].author.display_name	B. V. K. Vijaya Kumar
authorships[1].author_position	middle
authorships[1].raw_author_name	Bhagavatula, Vijayakumar
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A5029562156
authorships[2].author.orcid	https://orcid.org/0000-0002-7453-5759
authorships[2].author.display_name	Zhenyu Zhou
authorships[2].author_position	middle
authorships[2].raw_author_name	Zhou, Zhenyu
authorships[2].is_corresponding	False
authorships[3].author.id	https://openalex.org/A5104027966
authorships[3].author.orcid
authorships[3].author.display_name	Ajay Kumar
authorships[3].author_position	last
authorships[3].raw_author_name	Kumar, Ajay
authorships[3].is_corresponding	False
has_content.pdf	False
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://arxiv.org/pdf/2411.08642
open_access.oa_status	green
open_access.any_repository_has_fulltext	False
created_date	2024-11-16T00:00:00
display_name	Towards More Accurate Fake Detection on Images Generated from Advanced Generative and Neural Rendering Models
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T06:51:31.235846
primary_topic.id	https://openalex.org/T12357
primary_topic.field.id	https://openalex.org/fields/17
primary_topic.field.display_name	Computer Science
primary_topic.score	0.9994000196456909
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/1707
primary_topic.subfield.display_name	Computer Vision and Pattern Recognition
primary_topic.display_name	Digital Media Forensic Detection
related_works	https://openalex.org/W4365211920, https://openalex.org/W3014948380, https://openalex.org/W4380551139, https://openalex.org/W4317695495, https://openalex.org/W4395044357, https://openalex.org/W4287117424, https://openalex.org/W4387506531, https://openalex.org/W2087346071, https://openalex.org/W2967848559, https://openalex.org/W4299831724
cited_by_count	0
locations_count	2
best_oa_location.id	pmh:oai:arXiv.org:2411.08642
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S4306400194
best_oa_location.source.issn
best_oa_location.source.type	repository
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l
best_oa_location.source.is_core	False
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	arXiv (Cornell University)
best_oa_location.source.host_organization	https://openalex.org/I205783295
best_oa_location.source.host_organization_name	Cornell University
best_oa_location.source.host_organization_lineage	https://openalex.org/I205783295
best_oa_location.license
best_oa_location.pdf_url	https://arxiv.org/pdf/2411.08642
best_oa_location.version	submittedVersion
best_oa_location.raw_type
best_oa_location.license_id
best_oa_location.is_accepted	False
best_oa_location.is_published	False
best_oa_location.raw_source_name
best_oa_location.landing_page_url	http://arxiv.org/abs/2411.08642
primary_location.id	pmh:oai:arXiv.org:2411.08642
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S4306400194
primary_location.source.issn
primary_location.source.type	repository
primary_location.source.is_oa	True
primary_location.source.issn_l
primary_location.source.is_core	False
primary_location.source.is_in_doaj	False
primary_location.source.display_name	arXiv (Cornell University)
primary_location.source.host_organization	https://openalex.org/I205783295
primary_location.source.host_organization_name	Cornell University
primary_location.source.host_organization_lineage	https://openalex.org/I205783295
primary_location.license
primary_location.pdf_url	https://arxiv.org/pdf/2411.08642
primary_location.version	submittedVersion
primary_location.raw_type
primary_location.license_id
primary_location.is_accepted	False
primary_location.is_published	False
primary_location.raw_source_name
primary_location.landing_page_url	http://arxiv.org/abs/2411.08642
publication_date	2024-11-13
publication_year	2024
referenced_works_count	0
abstract_inverted_index.a	22, 95, 121, 130, 143
abstract_inverted_index.3D	18, 122
abstract_inverted_index.By	80
abstract_inverted_index.In	46
abstract_inverted_index.To	116
abstract_inverted_index.an	48
abstract_inverted_index.by	110, 137
abstract_inverted_index.in	3, 104
abstract_inverted_index.is	52
abstract_inverted_index.it	88
abstract_inverted_index.of	71, 120
abstract_inverted_index.to	25, 58, 76
abstract_inverted_index.we	93, 128
abstract_inverted_index.The	0
abstract_inverted_index.and	17, 27, 36, 85, 148
abstract_inverted_index.can	32
abstract_inverted_index.due	75
abstract_inverted_index.for	42, 146
abstract_inverted_index.its	77
abstract_inverted_index.the	40, 56, 63, 69, 73, 82, 111, 118
abstract_inverted_index.GANs	26
abstract_inverted_index.data	6
abstract_inverted_index.fake	125
abstract_inverted_index.from	62
abstract_inverted_index.like	13
abstract_inverted_index.need	41
abstract_inverted_index.that	54, 99, 133
abstract_inverted_index.with	9, 89
abstract_inverted_index.These	30
abstract_inverted_index.image	113, 126
abstract_inverted_index.model	57
abstract_inverted_index.Fields	16
abstract_inverted_index.Neural	14
abstract_inverted_index.create	94
abstract_inverted_index.domain	84, 91
abstract_inverted_index.images	35, 108, 135
abstract_inverted_index.latest	112
abstract_inverted_index.neural	10, 123, 139
abstract_inverted_index.offers	21
abstract_inverted_index.robust	43, 96, 144
abstract_inverted_index.visual	5
abstract_inverted_index.Fourier	64
abstract_inverted_index.absence	119
abstract_inverted_index.address	117
abstract_inverted_index.develop	129
abstract_inverted_index.diverse	138
abstract_inverted_index.enables	55
abstract_inverted_index.extract	59
abstract_inverted_index.methods	31
abstract_inverted_index.models.	29
abstract_inverted_index.produce	33
abstract_inverted_index.spatial	90
abstract_inverted_index.thereby	67
abstract_inverted_index.Gaussian	19
abstract_inverted_index.Radiance	15
abstract_inverted_index.avatars,	38
abstract_inverted_index.database	132
abstract_inverted_index.detector	98
abstract_inverted_index.features	61
abstract_inverted_index.includes	134
abstract_inverted_index.lifelike	37
abstract_inverted_index.methods.	45, 151
abstract_inverted_index.powerful	23
abstract_inverted_index.progress	2
abstract_inverted_index.proposed	53
abstract_inverted_index.spectral	83
abstract_inverted_index.spectrum	65, 74
abstract_inverted_index.superior	101
abstract_inverted_index.training	50
abstract_inverted_index.advancing	149
abstract_inverted_index.combining	87
abstract_inverted_index.database,	127
abstract_inverted_index.detection	44, 150
abstract_inverted_index.diffusion	28
abstract_inverted_index.generated	109, 136
abstract_inverted_index.providing	142
abstract_inverted_index.rendering	11, 140
abstract_inverted_index.response,	47
abstract_inverted_index.synthesis	114
abstract_inverted_index.synthetic	107
abstract_inverted_index.technique	51
abstract_inverted_index.challenges	70
abstract_inverted_index.especially	8
abstract_inverted_index.evaluating	147
abstract_inverted_index.foundation	145
abstract_inverted_index.leveraging	81
abstract_inverted_index.magnitude,	66
abstract_inverted_index.multimodal	97
abstract_inverted_index.overcoming	68
abstract_inverted_index.remarkable	1
abstract_inverted_index.splatting,	20
abstract_inverted_index.techniques	12
abstract_inverted_index.alternative	24
abstract_inverted_index.challenging	106
abstract_inverted_index.dynamically	86
abstract_inverted_index.generation,	7
abstract_inverted_index.identifying	105
abstract_inverted_index.properties.	79
abstract_inverted_index.techniques,	141
abstract_inverted_index.techniques.	115
abstract_inverted_index.capabilities	103
abstract_inverted_index.demonstrates	100
abstract_inverted_index.highlighting	39
abstract_inverted_index.information,	92
abstract_inverted_index.unsupervised	49
abstract_inverted_index.comprehensive	60, 131
abstract_inverted_index.high-fidelity	34
abstract_inverted_index.generalization	102
abstract_inverted_index.reconstructing	72
abstract_inverted_index.centrosymmetric	78
abstract_inverted_index.rendering-based	124
abstract_inverted_index.neural-network-driven	4
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	4
citation_normalized_percentile