Poster
in
Workshop: NeurIPS 2023 Workshop on Diffusion Models
LDM3D-VR: Latent Diffusion Model for 3D VR
Gabriela Ben-Melech Stan · Diana Wofk · Estelle Aflalo · Shao-Yen Tseng · zhipeng cai · Michael Paulitsch · VASUDEV LAL
Abstract:
Latent diffusion models have proven to be state-of-the-art in the creation and manipulation of visual outputs. However, as far as we know, the generation of depth maps jointly with RGB is still limited. We introduce LDM3D-VR, a suite of diffusion models targeting virtual reality development that includes LDM3D-pano and LDM3D-SR. These models enable the generation of panoramic RGBD based on textual prompts and the upscaling of low-resolution inputs to high-resolution RGBD, respectively. Our models are fine-tuned from existing pretrained models on datasets containing panoramic/high-resolution RGB images, depth maps and captions. Both models are evaluated in comparison to existing related methods.
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