mlsanityData to 14 Oct 2026

Dynamic Inverse Rendering for Enhanced Material-Lighting Decomposition

arXiv 2607.09329 ↗First posted 10 Jul 2026cs.CV cs.GRcited by 0

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Abstract (arXiv)

Decomposing outgoing surface radiance into material and illumination during inverse rendering is essential for applications such as relighting and augmented reality, yet it is severely ill-posed since multiple combinations can result in the same observed colour. Capturing an object under multiple lighting conditions usually helps resolve this ambiguity as it constrains the optimization towards correct solutions. In this work, we explore the potential of reconstructing rigidly moving objects -- which provides observations of diverse light-surface interactions -- to resolve the material-lighting ambiguity in inverse rendering. For this purpose, we introduce a relightable approach that marries object tracking and reconstruction with inverse rendering for general rigidly moving objects. Our experimental analysis on synthetic data demonstrates that motion can be an advantage for disentangling material and lighting: the reconstructed material is significantly more accurate when the object is observed under rigid motion than when it is static. Moreover, results on RGB videos of real hand-held objects show that our pipeline preserves this advantage even under noisy real-world conditions.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 49 of its 63 references that are in the map. First posted on arXiv 10 Jul 2026.

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49 of 63 references.

References · 49

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37 more
  1. 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 224
  2. 2023COLMAP-Free 3D Gaussian Splattingcited by 193
  3. 2023TensoIR: Tensorial Inverse Renderingcited by 168
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  36. 2025TensoFlow: Tensorial Flow-based Sampler for Inverse Renderingcited by 2
  37. 2025OnlineSplatter: Pose-Free Online 3D Reconstruction for Free-Moving Objectscited by 2

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