Are you ready to revolutionize stochastic segmentation? Dive into the latest breakthrough with Flow-SSN that’s changing the game for developers and engineers.
Key Facts about Flow-SSN:
- The flow’s prior is typically fixed, but Flow-SSN learns it to model pixel dependencies efficiently.
- Sampling (ODE solving) becomes more efficient without performance sacrifices.
- Bespoke training objectives for autoregressive and continuous-time flow variants are introduced.
- Flow-SSN achieves state-of-the-art performance on standard stochastic segmentation benchmarks.
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