IGF Bench: Indoor Geometric Fidelity Benchmark Anonymous mirror for NeurIPS 2026 Evaluations and Datasets Track double blind review. The de anonymised author/maintainer information will replace this header at camera ready. IGF Bench is the first benchmark for evaluating structural level geometric fidelity of conditionally generated indoor scene images, going beyond perceptual metrics like FID and LPIPS. It pairs 3,600 calibrated synthetic ground truth views with 21,600 generated images from six state of the art ControlNet models, plus 25,200 monocular depth estimates , all evaluated with four complementary geometric metrics: planarity ( L plane ) , orthogonality ( L ortho ) , edge alignment ( L edge ) , and vanishing point consistency ( L vp ) . Quick stats Value : : Calibrated GT views 3,600 (300 rooms × 3 complexity levels × 4 viewpoints) Paired generated images 21,600 (6 ControlNet models, all conditioned on identical Canny maps) Paired depth estimates 25,200 (DepthPro on all GT + generated; DAv2 / ZoeDepth subsets) Camera FOV 90° Render resolution 1024×1024 Total size ≈ 219 GB License CC BY NC SA 4.0 (data) + Apache 2.0 (code) Code repo Paper NeurIPS 2026 E&D Track (under revie…
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