15Five

20-20 Technologies is a comprehensive interior design and space planning software platform primarily serving kitchen and bath designers, furniture retailers, and interior design professionals. The company provides specialized tools for creating detailed 3D visualizations, generating accurate quotes, managing projects, and streamlining the entire design-to-sales workflow. Their software enables designers to create photorealistic renderings, produce precise floor plans, and automatically generate material lists and pricing. The platform integrates with manufacturer catalogs, allowing users to access up-to-date product information and specifications. 20-20 Technologies focuses on bridging the gap between design creativity and practical business needs, helping professionals present compelling visual proposals while maintaining accurate costing and project management. The software is particularly strong in the kitchen and bath industry, where precision measurements and material specifications are critical. Users range from independent designers to large retail chains and manufacturing companies seeking to improve their design presentation capabilities and sales processes.

3D Generative Adversarial Network (3D-GAN) is a pioneering research project and framework for generating three-dimensional objects using Generative Adversarial Networks. Developed primarily in academia, it represents a significant advancement in unsupervised learning for 3D data synthesis. The tool learns to create volumetric 3D models from 2D image datasets, enabling the generation of novel, realistic 3D shapes such as furniture, vehicles, and basic structures without explicit 3D supervision. It is used by researchers, computer vision scientists, and developers exploring 3D content creation, synthetic data generation for robotics and autonomous systems, and advancements in geometric deep learning. The project demonstrates how adversarial training can be applied to 3D convolutional networks, producing high-quality voxel-based outputs. It serves as a foundational reference implementation for subsequent work in 3D generative AI, often cited in papers exploring 3D shape completion, single-view reconstruction, and neural scene representation. While not a commercial product with a polished UI, it provides code and models for the research community to build upon.

3D Reconstruction AI is an advanced platform that transforms 2D images into detailed 3D models using artificial intelligence and computer vision technologies. The tool enables users to upload photographs of objects, scenes, or people and automatically generates textured 3D meshes suitable for various applications. It serves professionals in architecture, gaming, virtual reality, e-commerce, and cultural heritage preservation who need efficient 3D modeling solutions without extensive manual labor. The platform addresses the time-consuming and expensive nature of traditional 3D modeling by providing automated reconstruction that maintains geometric accuracy and visual fidelity. Users can process single images or multiple views to create complete 3D assets ready for export to standard formats like OBJ, FBX, or GLTF. The service operates through a web interface and API, making it accessible to both technical and non-technical users seeking to digitize physical objects or environments for digital workflows.