Image and video generation AI system development

basic information

Scope of Services - System development for image generation AI, video generation AI, and 3D model generation AI (from requirements definition to learning, implementation, and operation) Target Outputs (Examples) - Video: Short video generation, partial video generation/editing, style transfer - 3D: 3D model generation (method selection based on application: NeRF, Gaussian Splatting, etc.) Service Details (Processes) - Research on related papers and existing methods / technology selection - Implementation of proprietary diffusion models, etc. (LoRA, fine-tuning, conditional generation, etc.) - Learning and evaluation (design of quality metrics, ensuring reproducibility, hyperparameter tuning) - System construction and deployment (API creation, integration with web/business systems, operational design) Delivery Formats - Contract development / Proof of Concept / Joint research / Integration into existing systems Execution Environment - Cloud (AWS/GCP/Azure) or on-premises (proposed based on requirements) - Support for learning and inference in GPU environments Deliverables (Examples) - Trained models (or inference packages) - Inference API/UI (as needed) - Learning and evaluation reports, design documents, operational manuals

Price information

Price: Individual Estimate - It varies depending on requirements (target for generation, quality standards, whether learning is involved, data status, operational form). - First, we will conduct a hearing and then provide a rough estimate.

Delivery Time

Applications/Examples of results

Uses (Examples) - Product and Advertising Creative Generation: Generating variations of product images, background replacement, style unification - Design/Planning Support: Generating concept art, mass production of rough drafts, creating mood boards - Video Content Generation and Editing: Generating short videos, style transformation of existing videos, partial generation - 3D Production Support: Generating/restoring 3D models, generating textures (methods selected based on requirements) - Internal Business Efficiency: Integrating generative AI into existing systems to streamline production workflows Examples of Achievements (Publicly Shareable Scope) - For image generation AI applications - Training of diffusion model systems (including fine-tuning) - Speeding up and optimizing inference code (bottleneck analysis, implementation improvements, inference pipeline adjustments, etc.) *Details can be shared within the scope of an NDA Initiatives/Verification Achievements - Researching the latest papers in image and video generation and implementing reproductions - Verifying and improving generative models from GitHub/OSS (such as diffusion models) - Validating a complete development process from data preparation to training, evaluation, and inference API creation in-house - Based on experience in AI/system development including image processing, video processing, and 3D processing, capable of promoting projects including requirements definition and operation.