MATH · IN · MODELS

Self-supervised NaviNeRF finds dimension-restricted semantic directions in StyleNeRF W+

measured in 1 paper

Xie et al. train a self-supervised Navigator that discovers interpretable semantic directions in the W+ latent space of a real StyleNeRF 3D-aware generator [xie-etal-2023-navinerf-latent-semantic-navigation] Restricting shifts to the fine-grained 9th-18th dimensions of the 18-vector W+ style code outperforms shifting all 18 dimensions for disentangled attribute control [xie-etal-2023-navinerf-latent-semantic-navigation] Using the full W+ space (18 per-layer style vectors) outperforms the single-vector W space for fine-grained disentanglement [xie-etal-2023-navinerf-latent-semantic-navigation] NaviNeRF's FID/KID is competitive with its StyleNeRF backbone and far ahead of pi-GAN and GIRAFFE, extending 2D-latent direction discovery to a 3D generative space [xie-etal-2023-navinerf-latent-semantic-navigation]

Context

StyleNeRF W+ latent-direction discovery, dimension-restricted vs. full-space shifting ablation, 3D-aware generative latent space

Papers

NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigation — Xie, Baao, Li, Bohan, Zhang, Zequn, Dong, Junting, Jin, Xin, Yang, Jingyu, Zeng, Wenjun2023 · arXiv:2304.11342