Carnegie Mellon University · Rendering Refinement

FixAnything

Repairs rendering artefacts in sparse-view 3D representations — 3DGS, NeRF, mesh or point cloud — by fine-tuning Wan2.1-I2V-14B with rank-64 LoRA adapters. Stage one trains jointly across all four representations on paired DL3DV-10K videos using a per-frame preserve/repair mask; stage two applies geometry-aware Flow-DPO preference optimisation with COLMAP-measured camera-pose accuracy as the reward signal. Pose accuracy rises from 61.1 to 68.3 AUC@5 degrees through DPO, and it generalises to MipNeRF-360 and LLFF on roughly 20 paired fine-tuning videos while training about 1% of parameters. ECCV 2026, code released.