Trajectory Constraints for Imaging Inverse Problems
Diffusion models have achieved strong performance in imaging inverse problems, but typically rely on domain-matched pretrained models and external training data. Moreover, errors introduced at intermediate reverse-sampling steps can accumulate and degrade the final reconstruction, with their propagation strongly influenced by how successive states are related. We propose TRACE, a training-free TRAjectory-Constrained rEconstruction framework for imaging inverse problems. TRACE replaces the pretrained diffusion model with an untrained overparameterized network optimized directly from the observed measurements and organizes reconstruction as a sequence of intermediate states. At each step, T...
| Authors | Chaoyan Huang, Haijie Yuan, Bharath Subramanian et al. |
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| Primary category | cs.CV |
| Published | 27 May 2026 |
| Last updated at source | 12 October 2026 |
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