update

app.py

@@ -364,7 +364,7 @@ def main(args):
 
             ## How does it work?
 
-            LN3Diff is a feedforward 3D Latent Diffusion Model that supports direct 3D asset generation via diffusion sampling. 
+            LN3Diff is a native 3D Latent Diffusion Model that supports direct 3D asset generation via diffusion sampling. 
             Compared to SDS-based ([DreamFusion](https://dreamfusion3d.github.io/)), mulit-view generation-based ([MVDream](https://arxiv.org/abs/2308.16512), [Zero123++](https://github.com/SUDO-AI-3D/zero123plus), [Instant3D](https://instant-3d.github.io/)) and feedforward 3D reconstruction-based ([LRM](https://yiconghong.me/LRM/), [InstantMesh](https://github.com/TencentARC/InstantMesh), [LGM](https://github.com/3DTopia/LGM)), 
             LN3Diff supports feedforward 3D generation with a unified framework.
             Like 2D/Video AIGC pipeline, LN3Diff first trains a 3D-VAE and then conduct LDM training (text/image conditioned) on the learned latent space. Some related methods from the industry ([Shape-E](https://github.com/openai/shap-e), [CLAY](https://github.com/CLAY-3D/OpenCLAY), [Meta 3D Gen](https://arxiv.org/abs/2303.05371)) also follow the same paradigm.