HUAWEI Bayer Lab, EPFL & Bologna · Marigold V2 Depth

Marigold V2

Repurposes a pretrained image-editing diffusion transformer, Qwen-Image-Edit, into single-step dense predictors covering depth, see-through depth, surface normals and albedo, using representation alignment against ground-truth semantic features plus a two-stage fine-tune built on a Sinkhorn loss. The practical claim is the training budget: under a week on one 32GB GPU. Reports a 16-26% cut in AbsRel over the prior best on KITTI and ETH3D, with visible gains on fur, foliage and hair-thin edges. SIGGRAPH Asia 2026, with a live web demo.