GAP3D: Generative Alignment of VLM Latents to Patch-Level Embeddings for 3D Generation 事件

GAP3D: Generative Alignment of VLM Latents to Patch-Level Embeddings for 3D Generation arXiv:2605.28995v1 Announce Type: new Abstract: Recent approaches integrating vision-language models (VLMs) as prompt encoders for generative model conditioning typically rely on expensive end-to-end training or map features to compressed representations, discarding the dense spatial structure required for geometry-aware tasks like 3D asset generation. To address this, we propose GAP3D, a modular, diffusion-b