AI & ML
Pygmalion Effect in Vision: Image-to-Clay Translation for Reflective Geometry Reconstruction
arXiv cs.GR0 views
arXiv:2511.21098v2 Announce Type: replace-cross Abstract: Understanding reflection remains a long-standing challenge in 3D reconstruction due to the entanglement of appearance and geometry under view-dependent reflections. In this work, we present the Pygmalion Effect in Vision, a novel framework that metaphorically "sculpts" reflective objects into clay-like forms through image-to-clay translation. We then introduce a dual-branch design in which a BRDF-based reflective branch and a clay-guided branch share the same Gaussian geometry but operate through independent rendering paths. The clay-guided branch, supervised by the synthesized clay images, provides reflection-free geometric guidance that complements the photometric supervision of the BRDF branch. Experiments on both synthetic and real datasets show consistent improvements in both geometry and photometric metrics. Beyond technical gains, our framework reveals that seeing by unshining, translating radiance into neutrality, can serve as a powerful inductive bias for reflective object geometry learning.
Source:https://arxiv.org/abs/2511.21098PreviousPhysics-Driven Extraction of Dynamic Fluid Asset from Monocular Video with Generative 3DGSNextToken Importance-Aware Semantic Communication Enabled Robust Video Transmission
Related posts
Author or just ‘acknowledged’? How women are not gaining full credit for research
0Nature News
The Best iPad to Buy (and What to Avoid) in 2026: Air, Pro, Mini
0Wired
A Better Image Model Still Needs a Better Assignment
0dev.to
Review an AI Image by the Work It Leaves Behind
0dev.to

Don't eyeball AI-generated product images. Test the text like CI.
0dev.to

An Updated Image Needs a Cache Plan, Not Another Upload
0dev.to