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Featuring Professor Antonio Torralba, MITRecorded live at the IEEE International Conference on Image Processing (ICIP 2025)Modern computer vision relies on vast image datasets—but collecting and labeling those images comes at a high cost. What if AI systems could learn from synthetically generated images—even ones that look like abstract art with no recognizable objects?
In this SPS Distinguished Industry Lecturer highlight, NVIDIA’s Morteza Mardani shares a practical, task-agnostic way to use diffusion models for image restoration and reconstruction—without retraining foundation models.
The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.