Reviews: Multi-objects Generation with Amortized Structural Regularization
–Neural Information Processing Systems
Let me begin by stating that my judgement is based on assuming the the derivations are mathematically correct - though I attempted at verifying, I am not certain if everything is free of error. With that in mind: Originality: I believe the central idea of the work is novel, and the derivation is unseen, at least to my limited knowledge of related work. However, the generative model involved (AIR) is borrowed directly from related work, and there have definitely been prior work attempting to regularize the posterior. Though the idea of using structural knowledge to directly shape the distribution of interpretable posteriors such as size and number of objects is novel, I am not so sure if this idea is generalizable enough (see quality and significance section) to warrant a major original contribution. Quality: I believe the derivation is technically sound, though I have not verified the mathematical details and cannot be sure if it is free of errors.
Neural Information Processing Systems
Jan-26-2025, 05:03:28 GMT
- Technology: