Our team is pioneering new methods to transform visual content creation and processing. By integrating state-of-the-art AI models with computational imaging techniques, we aim to push the boundaries of photography and video technology.

Ongoing Research

  1. Super-Resolution Imaging
    • Objective: Develop AI algorithms to upscale low-resolution images and videos with enhanced clarity and detail.
    • Progress: Achieved a 25% improvement in edge sharpness and texture consistency using advanced diffusion models.
  2. AI-Assisted Photo Restoration
    • Objective: Restore and colorize historical and damaged photographs using deep learning.
    • Progress: Created a novel GAN-based pipeline capable of reconstructing heavily degraded images with over 90% accuracy.
  3. Real-Time Computational Optics
    • Objective: Improve camera systems for low-light and HDR photography.
    • Progress: Developed an adaptive algorithm that dynamically adjusts exposure and contrast, enabling real-time HDR rendering with minimal artifacts.
  4. Generative Visual Content
    • Objective: Use generative AI to create photorealistic images and scenes from textual descriptions.
    • Progress: Implemented a text-to-image model with 80% higher fidelity compared to existing systems, revolutionizing creative content generation.
  5. AI-Powered Video Processing
    • Objective: Enhance video stabilization, frame interpolation, and color grading.
    • Progress: Deployed a neural network capable of 2x real-time frame interpolation for smoother playback and dynamic scene adjustments.

Key Results and Milestones

  • Super-Resolution Breakthroughs: Achieved industry-leading performance in image quality benchmarks for super-resolution tasks.
  • Real-Time Applications: Successfully integrated AI-based computational photography tools into smartphone cameras for instant enhancements.
  • Generative Art Tools: Partnered with creative industries to deploy generative AI tools, enabling artists to create photorealistic scenes with minimal input.
  • Medical Imaging Impact: Applied restoration techniques to improve the clarity of X-ray and MRI images, aiding faster and more accurate diagnostics.

Future Directions

We continue to explore novel approaches to:

  • Develop lightweight AI models for deployment on edge devices.
  • Innovate augmented reality (AR) tools for immersive photo and video editing.
  • Advance ethical AI practices to ensure fairness and transparency in generative and computational imaging technologies.

Researchers