Figure 2. Approach Overview. We first pre-train a reconstruction model using multi-view renderings of synthetic data. We then self-train
category-specific models on diverse image collections in-the-wild with only foreground mask annotations. We finally distill the learned
models from prior training stages into a unified reconstruction model.