arXiv Artificial Intelligence

Albedo Estimation via Latent Bridge Matching

1 hour ago 11.09.2026 07:00 👁 2 views
Albedo Estimation via Latent Bridge Matching

Quick summary

arXiv:2609.09884v1 Announce Type: cross Abstract: Recent advances in Intrinsic Image Decomposition (IID) have increasingly relied on generative models. However, progress remains limited by three key challenges: (a) insufficient physical consistency, (b) high computational cost at inference time, and (c) limited generalization capabilities. In this work, we show that latent bridge matching (LBM) effectively addresses these limitations for albedo estimation. We introduce a novel LBM-based architecture that enforces physical consistency through a pixel reconstruction loss, benefits from the inher

Key takeaways

  • arXiv:2609.09884v1 Announce Type: cross Abstract: Recent advances in Intrinsic Image Decomposition (IID) have increasingly relied on generative models.
  • However, progress remains limited by three key challenges: (a) insufficient physical consistency, (b) high computational cost at inference time, and (c) limited generalization capabilities.
  • In this work, we show that latent bridge matching (LBM) effectively addresses these limitations for albedo estimation.

Why it matters

“Albedo Estimation via Latent Bridge Matching” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗