3D 자산 생성 및 텍스처링용 AI 시장 : 시장 규모, 점유율 및 예측 - 자산 유형별, AI 모델별, 통합별, 최종 사용자별(게임, 메타버스, VFX) 예측(2026-2036년)
AI for 3D Asset Generation & Texturing Market Size, Share, & Forecast by Asset Type, AI Model, Integration, and End-User (Games, Metaverse, VFX) - Global Forecast (2026-2036)
상품코드:1936222
리서치사:Meticulous Research
발행일:On Demand Report
페이지 정보:영문 293 Pages
라이선스 & 가격 (부가세 별도)
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한글목차
3D 자산 생성 및 텍스처링용 AI 시장은 2026-2036년 예측 기간 동안 CAGR 20.8%로 성장할 전망이며, 2036년까지 128억 4,000만 달러에 달할 것으로 예측되고 있습니다. 이 보고서는 세계 5대 지역에서 AI 3D 자산 생성 시장의 상세한 분석을 제공하며, 현재 시장 동향, 시장 규모, 최근 동향, 2036년까지의 예측에 중점을 두고 있습니다. 광범위한 2차와 1차 조사 및 시장 시나리오의 상세한 분석을 통해 주요 산업의 촉진요인, 억제요인, 기회 및 과제의 영향 분석을 실시했습니다. 이 시장의 성장은 엄청난 양의 3D 컨텐츠를 필요로 하는 게임 산업의 폭발적 성장, 몰입형 가상 세계를 요구하는 메타버스 플랫폼 대두, 제작 효율화를 목적으로 한 시각 효과 스튜디오에서 AI 도입, 3D 자산 제작 시간 및 비용 절감의 필요성, 그리고 인디 개발자와 소규모 스튜디오를 위한 3D 컨텐츠 제작의 민주화 또한 텍스트에서 3D로의 확산 모델, 신경 래디언스 필드(NeRF), 절차형 생성 알고리즘 등 AI 모델의 진보, 플러그인과 API를 통한 전문가용 3D 소프트웨어에 AI 생성 툴의 통합, AI를 활용한 텍스처 머티리얼 생성 기술의 개발, 그리고 프로페셔널한 제작 파이프라인에서의 AI 생성 자산의 수용 확대가 시장 성장을 지지할 것으로 전망됩니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
자산 유형별 시장 분석
AI 모델 유형별 시장 분석
텍스처링 기능별 시장 분석
통합 유형별 시장 분석
최종 사용자별 시장 분석
도입 모델별 시장 분석
가격 모델별 시장 분석
출력 형식별 시장 분석
지역별 시장 분석
경쟁 분석
제4장 시장 인사이트
시장 성장 촉진요인(2026-2036년)
게임 산업에 있어서 자산 수요 급증
메타버스 개발 및 가상 세계 구축
3D 자산 제작의 비용 절감
시장 성장 억제요인(2026-2036년)
품질 및 일관성의 제약
기술적 복잡성 및 통합 과제
시장 기회(2026-2036년)
VFX 및 영화 제작의 가속
엔터테인먼트 분야를 넘은 기업용 용도
시장 과제(2026-2036년)
아티스트 업계의 저항 및 워크플로의 혼란
저작권 및 교육 데이터에 대한 우려
시장 동향(2026-2036년)
텍스트에서 3D로의 확산 모델 진화
전문 3D 소프트웨어와의 통합
Porter's Five Forces 분석
제5장 AI 3D 생성 기술 및 아키텍처
신경방사장(NeRF)
텍스트에서 3D로의 확산 모델
텍스처 생성을 위한 GAN
점군 처리
절차형 생성 알고리즘
PBR 머티리얼 생성
메쉬 최적화 및 토폴로지
실시간 렌더링 통합
시장에 미치는 영향
제6장 경쟁 구도
주요 성장 전략
경쟁 대시보드
벤더의 시장 포지셔닝
주요 기업별 시장 점유율
제7장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 자산 유형별
캐릭터 및 생물
휴머노이드 캐릭터
판타지 생물
아바타 및 디지털 휴먼
환경 및 경관
자연 환경
도시 환경
SF 및 판타지의 세계
소품 및 물체
가구 및 인테리어
차량 및 기계
장식 요소
건물 및 아키텍처
주택 건축
상업 시설
역사적 및 환상적인 아키텍처
식물 및 유기적 요소
나무 및 식물
지형 및 경관
유기 텍스처
제8장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : AI 모델 유형별
텍스트에서 3D로의 확산 모델
NeRF 기반 모델
GAN 기반 생성
절차형 AI 시스템
하이브리드 모델
제9장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 텍스처링 기능별
PBR 머티리얼 생성
절차적 텍스처 합성
이미지를 텍스처로 변환
스타일 전송 텍스처링
AI 지원에 의한 수동 텍스처링
제10장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 통합 유형별
플러그인 통합
Blender 플러그인
Unity/Unreal 통합
Maya/3ds Max 플러그인
독립형 웹 플랫폼
데스크톱 용도
API 및 SDK 통합
게임 엔진 네이티브 툴
제11장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 최종 사용자별
게임 개발자
AAA 스튜디오
인디 개발자
모바일 게임 개발자
메타버스 및 가상 세계 플랫폼
VFX 및 영화 제작
아키텍처 및 부동산
제품 디자인 및 전자상거래
교육 및 연수
광고 및 마케팅
제12장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 전개 모드별
클라우드 기반
온프레미스
하이브리드 도입
제13장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 가격 모델별
구독형
자산별 가격 설정
프리미엄
엔터프라이즈 라이선싱
제14장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 출력 포맷별
게임 대응 에셋(FBX, GLTF)
CAD 포맷
렌더링 형식(OBJ, USD)
점군 데이터 및 메쉬
소스 파일(Blend, Maya)
제15장 세계의 3D 자산 생성 및 텍스처링용 AI 시장 : 지역별
북미
미국
캐나다
멕시코
유럽
영국
독일
프랑스
북유럽 국가
기타 유럽
아시아태평양
중국
일본
한국
인도
동남아시아
기타 아시아태평양
라틴아메리카
중동 및 아프리카
제16장 기업 프로파일(사업 개요, 제품 포트폴리오, 전략적 전개, SWOT 분석)
NVIDIA(GET3D)
Kaedim
Masterpiece Studio
Luma AI
Meshy
Scenario
Leonardo.ai
Sloyd
Promethean AI
Runway ML
Poly(Google)
DeepMotion
Ready Player Me
Polycam
3DFY
Spline AI
Krikey AI
Kinetix
CommonSim
Others
제17장 부록
AJY
영문 목차
영문목차
AI for 3D Asset Generation & Texturing Market by Asset Type, AI Model (Text-to-3D, NeRF, Diffusion), Integration, and End-User (Games, Metaverse, VFX) - Global Forecasts (2026-2036)
According to the research report titled, 'AI for 3D Asset Generation & Texturing Market by Asset Type, AI Model (Text-to-3D, NeRF, Diffusion), Integration, and End-User (Games, Metaverse, VFX) - Global Forecasts (2026-2036),' the AI for 3D asset generation and texturing market is projected to reach USD 12.84 billion by 2036, at a CAGR of 20.8% during the forecast period 2026-2036. The report provides an in-depth analysis of the global AI 3D asset generation market across five major regions, emphasizing the current market trends, market sizes, recent developments, and forecasts till 2036. Following extensive secondary and primary research and an in-depth analysis of the market scenario, the report conducts the impact analysis of the key industry drivers, restraints, opportunities, and challenges. The growth of this market is driven by the explosive growth of the gaming industry requiring massive volumes of 3D content, the emergence of metaverse platforms demanding immersive virtual worlds, the adoption of AI by visual effects studios to accelerate production, the need to reduce 3D asset creation time and costs, and the democratization of 3D content creation for indie developers and small studios. Moreover, the advancement of AI models including text-to-3D diffusion models, Neural Radiance Fields (NeRF), and procedural generation algorithms, the integration of AI generation tools into professional 3D software through plugins and APIs, the development of AI-powered texture and material generation, and the increasing acceptance of AI-generated assets in professional production pipelines are expected to support the market's growth.
Key Players
The key players operating in the AI for 3D asset generation and texturing market are OpenAI (U.S.), Google DeepMind (U.K./U.S.), Meta Platforms Inc. (U.S.), NVIDIA Corporation (U.S.), Adobe Inc. (U.S.), Autodesk Inc. (U.S.), Stability AI (U.K.), Runway ML (U.S.), Blockade Labs (U.S.), Loom.ai (U.S.), and others.
Market Segmentation
The AI for 3D asset generation and texturing market is segmented by asset type (characters, environments and props, vehicles, architectural elements, and others), AI model (text-to-3D diffusion models, Neural Radiance Fields (NeRF), procedural generation, and others), integration (standalone software, plugin and API integration, and cloud-based services), end-user (game developers, metaverse platforms, VFX studios, architectural visualization, and others), deployment model (cloud-based, on-premises, and hybrid), and geography. The study also evaluates industry competitors and analyzes the market at the country level.
Based on Asset Type
Based on asset type, the environment and props segment is estimated to hold the largest share of the market in 2026. This segment's dominance is primarily attributed to high volume requirements for game levels and metaverse worlds, relatively simpler geometry making them ideal for AI generation, and widespread demand across gaming and architectural visualization. Conversely, the character generation segment is expected to grow at the highest CAGR during the forecast period, driven by increasing sophistication of AI models in handling complex character topology and rigging requirements.
Based on AI Model
Based on AI model, the text-to-3D diffusion models segment is estimated to dominate the market in 2026. This segment's leadership is primarily driven by intuitive natural language interfaces enabling non-technical creators, rapid advancement in model capabilities, and accessibility for indie developers and small studios. The Neural Radiance Fields (NeRF) segment is expected to grow at a significant CAGR, driven by superior photorealism quality and suitability for high-end VFX and architectural visualization applications.
Based on Integration
Based on integration, the plugin and API integration segment is expected to account for the largest share of the market in 2026. This segment's dominance is driven by seamless workflow integration with existing professional 3D software like Blender, Maya, and Unreal Engine, professional user preference for familiar tools, and the established developer ecosystem. The cloud-based services segment is expected to grow at the highest CAGR, driven by increasing adoption of cloud workflows and accessibility for distributed teams.
Based on End-User
Based on end-user, the game developers segment is expected to witness the highest growth during the forecast period. This growth is driven by exploding demand for 3D content in games, indie studio budget constraints making AI solutions attractive, and the need for rapid iteration and prototyping. The VFX studios segment is expected to maintain a significant share, driven by adoption of AI for accelerating pre-visualization and asset creation in professional production pipelines.
Geographic Analysis
An in-depth geographic analysis of the industry provides detailed qualitative and quantitative insights into the five major regions (North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa) and the coverage of major countries in each region. In 2026, North America is estimated to account for the largest share of the global AI 3D asset generation market, driven by concentration of major game studios and VFX companies, leading AI research institutions and startups, early adoption by metaverse platforms, and strong venture capital investment in generative AI technologies. Asia-Pacific is projected to register the highest CAGR during the forecast period, fueled by massive gaming industry expansion in China, South Korea, and Japan, growing mobile game development ecosystem, metaverse initiatives from regional tech giants, and cost-conscious indie developer adoption. The region's rapid digital transformation and gaming industry growth are creating substantial market opportunities.
Key Questions Answered in the Report-
What is the current revenue generated by the AI for 3D asset generation and texturing market globally?
At what rate is the global AI for 3D asset generation and texturing demand projected to grow for the next 7-10 years?
What are the historical market sizes and growth rates of the global AI for 3D asset generation and texturing market?
What are the major factors impacting the growth of this market at the regional and country levels? What are the major opportunities for existing players and new entrants in the market?
Which segments in terms of asset type, AI model, integration, and end-user are expected to create major traction for the manufacturers in this market?
What are the key geographical trends in this market? Which regions/countries are expected to offer significant growth opportunities for the companies operating in the global AI for 3D asset generation and texturing market?
Who are the major players in the global AI for 3D asset generation and texturing market? What are their specific product offerings in this market?
What are the recent strategic developments in the global AI for 3D asset generation and texturing market? What are the impacts of these strategic developments on the market?
Scope of the Report:
AI for 3D Asset Generation & Texturing Market Assessment -- by Asset Type
Characters
Environments and Props
Vehicles
Architectural Elements
Other Asset Types
AI for 3D Asset Generation & Texturing Market Assessment -- by AI Model
Text-to-3D Diffusion Models
Neural Radiance Fields (NeRF)
Procedural Generation
Other Models
AI for 3D Asset Generation & Texturing Market Assessment -- by Integration
Standalone Software
Plugin and API Integration
Cloud-Based Services
AI for 3D Asset Generation & Texturing Market Assessment -- by End-User
Game Developers
Metaverse Platforms
VFX Studios
Architectural Visualization
Other End-Users
AI for 3D Asset Generation & Texturing Market Assessment -- by Deployment Model
Cloud-Based
On-Premises
Hybrid
AI for 3D Asset Generation & Texturing Market Assessment -- by Geography
North America
U.S.
Canada
Europe
U.K.
Germany
France
Spain
Italy
Rest of Europe
Asia-Pacific
China
Japan
South Korea
India
Australia & New Zealand
Rest of Asia-Pacific
Latin America
Mexico
Brazil
Argentina
Rest of Latin America
Middle East & Africa
Saudi Arabia
UAE
South Africa
Rest of Middle East & Africa
TABLE OF CONTENTS
1. Introduction
1.1. Market Definition
1.2. Market Ecosystem
1.3. Currency and Limitations
1.4. Key Stakeholders
2. Research Methodology
2.1. Research Approach
2.2. Data Collection & Validation
2.3. Market Assessment
2.4. Assumptions for the Study
3. Executive Summary
3.1. Overview
3.2. Market Analysis by Asset Type
3.3. Market Analysis by AI Model Type
3.4. Market Analysis by Texturing Capability
3.5. Market Analysis by Integration Type
3.6. Market Analysis by End-User
3.7. Market Analysis by Deployment Model
3.8. Market Analysis by Pricing Model
3.9. Market Analysis by Output Format
3.10. Market Analysis by Geography
3.11. Competitive Analysis
4. Market Insights
4.1. Introduction
4.2. Market Drivers (2026-2036)
4.2.1. Gaming Industry Asset Demand Explosion
4.2.2. Metaverse Development and Virtual World Construction
4.2.3. Cost Reduction in 3D Asset Production
4.3. Market Restraints (2026-2036)
4.3.1. Quality and Consistency Limitations
4.3.2. Technical Complexity and Integration Challenges
4.4. Market Opportunities (2026-2036)
4.4.1. VFX and Film Production Acceleration
4.4.2. Enterprise Applications Beyond Entertainment
4.5. Market Challenges (2026-2036)
4.5.1. Artist Industry Resistance and Workflow Disruption
4.5.2. Copyright and Training Data Concerns
4.6. Market Trends (2026-2036)
4.6.1. Text-to-3D Diffusion Model Advancement
4.6.2. Integration with Professional 3D Software
4.7. Porter's Five Forces Analysis
5. AI 3D Generation Technology and Architectures
5.1. Neural Radiance Fields (NeRFs)
5.2. Text-to-3D Diffusion Models
5.3. GANs for Texture Generation
5.4. Point Cloud Processing
5.5. Procedural Generation Algorithms
5.6. PBR Material Generation
5.7. Mesh Optimization and Topology
5.8. Real-Time Rendering Integration
5.9. Impact on Market
6. Competitive Landscape
6.1. Introduction
6.2. Key Growth Strategies
6.3. Competitive Dashboard
6.4. Vendor Market Positioning
6.5. Market Share by Key Players
7. Global AI 3D Asset Generation Market by Asset Type
7.1. Characters and Creatures
7.1.1. Humanoid Characters
7.1.2. Fantasy Creatures
7.1.3. Avatars and Digital Humans
7.2. Environments and Landscapes
7.2.1. Natural Environments
7.2.2. Urban Environments
7.2.3. Sci-Fi and Fantasy Worlds
7.3. Props and Objects
7.3.1. Furniture and Interiors
7.3.2. Vehicles and Machinery
7.3.3. Decorative Elements
7.4. Buildings and Architecture
7.4.1. Residential Buildings
7.4.2. Commercial Structures
7.4.3. Historical and Fantasy Architecture
7.5. Vegetation and Organic Assets
7.5.1. Trees and Plants
7.5.2. Terrain and Landscapes
7.5.3. Organic Textures
8. Global AI 3D Asset Generation Market by AI Model Type
8.1. Text-to-3D Diffusion Models
8.2. NeRF-Based Models
8.3. GAN-Based Generation
8.4. Procedural AI Systems
8.5. Hybrid Models
9. Global AI 3D Asset Generation Market by Texturing Capability
9.1. PBR Material Generation
9.2. Procedural Texture Synthesis
9.3. Image-to-Texture Conversion
9.4. Style Transfer Texturing
9.5. AI-Assisted Manual Texturing
10. Global AI 3D Asset Generation Market by Integration Type
10.1. Plugin Integration
10.1.1. Blender Plugins
10.1.2. Unity/Unreal Integration
10.1.3. Maya/3ds Max Plugins
10.2. Standalone Web Platforms
10.3. Desktop Applications
10.4. API and SDK Integration
10.5. Game Engine Native Tools
11. Global AI 3D Asset Generation Market by End-User
11.1. Game Developers
11.1.1. AAA Studios
11.1.2. Indie Developers
11.1.3. Mobile Game Developers
11.2. Metaverse and Virtual World Platforms
11.3. VFX and Film Production
11.4. Architecture and Real Estate
11.5. Product Design and E-Commerce
11.6. Education and Training
11.7. Advertising and Marketing
12. Global AI 3D Asset Generation Market by Deployment Model
12.1. Cloud-Based
12.2. On-Premise
12.3. Hybrid Deployment
13. Global AI 3D Asset Generation Market by Pricing Model
13.1. Subscription-Based
13.2. Per-Asset Pricing
13.3. Freemium
13.4. Enterprise Licensing
14. Global AI 3D Asset Generation Market by Output Format
