【Features】 - Supports image, video, and 3D generation using diffusion models, NeRF, Gaussian Splatting, and more. - Investigates the latest generative AI models and consistently handles research, implementation, and evaluation according to requirements. - Develops high-precision generation and reconstruction systems by leveraging expertise in image analysis, video analysis, and 3D analysis. - Capable of handling everything from prototypes for research purposes to system development aimed at practical operation. - Supports the design of learning, inference, quality evaluation, and improvement cycles for generative models. 【Our Strengths】 We are engaged in contract development and our own product offerings related to artificial intelligence. Since 2013, we have shifted to Deep Learning and have been working on improvements to CNNs and RNNs. We have a track record of leading the industry since the dawn of GANs and have experience writing for Shuwa System in the early days. Please feel free to contact us with your requests.

【Price Information】 - Prices will be individually quoted based on the target theme, required generation accuracy, presence of research elements, and scope of development. - We will flexibly respond from PoC and prototype development to full-scale implementation, proposing the optimal configuration according to your requests and budget. - Please feel free to contact us for more details.

The delivery time varies depending on the content, but prompt response is possible.

DiFarsion

【Applications and Achievements】 - Development of a 3D generation system utilizing Score Distillation Sampling After researching the latest technologies related to diffusion models and NeRF models, we developed a 3D generation system using Score Distillation Sampling. We validated and implemented a mechanism to generate high-quality 3D representations while leveraging insights from 2D generation models. - Acceleration of training and inference in diffusion-based image generation applications In image generation applications using diffusion models, we implemented processing acceleration during both training and inference. By optimizing the model structure, inference flow, and implementation methods, we worked on improving response speed and usability with an eye toward practical operation. - Fast video generation utilizing Gaussian Splatting We researched and developed a video generation system capable of fast rendering and generation using Gaussian Splatting. By leveraging the strengths of 3D representation, we built a mechanism that operates more lightweight and faster than conventional methods, deploying it as a highly practical generation technology.