4e582b104248a396a703646755071329-Paper-Datasets_and_Benchmarks_Track.pdf

Ho can wev intuiti er, can vely adv compose anced AI and image arrange generators scenes plan in the scenes 3D space with for similar photog3D spatial GenSpace, awareness a novel when benchmark creating and images evaluation from te pipeline xt or image to comprehensi prompts? W vely e present assess the spatial awareness of current image generation models. Furthermore, standard e ture valuations the detailed using spatial general errors. Vision-Language To handle this Models challenge, (VLMs) we propose frequently a speciali fail to capzed e tiple valuation visual pipeline foundation and models metric, and which pro reconstructs vides a more 3D accurate scene geometry and human-aligned using mulmetric of spatial faithfulness. Our findings show that while AI models create visually specific 3D appealing details images like object and can placement, follow general relationships, instructions, and measurements.