Submitted by SpatialComputing t3_yn1n7c in MachineLearning
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SpatialComputing OP t1_iv6jn6t wrote
>In order for learning systems to be able to understand and create 3D spaces, progress in generative models for 3D is sorely needed. The quote "The creation continues incessantly through the media of humans." is often attributed to Antoni Gaudí, who we pay homage to with our method’s name. We are interested in generative models that can capture the distribution of 3D scenes and then render views from scenes sampled from the learned distribution. Extensions of such generative models to conditional inference problems could have tremendous impact in a wide range of tasks in machine learning and computer vision. For example, one could sample plausible scene completions that are consistent with an image observation, or a text description (see Fig. 1 for 3D scenes sampled from GAUDI). In addition, such models would be of great practical use in model-based reinforcement learning and planning [12], SLAM [39], or 3D content creation. > >We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera. We tackle this challenging problem with a scalable yet powerful approach, where we first optimize a latent representation that disentangles radiance fields and camera poses. This latent representation is then used to learn a generative model that enables both unconditional and conditional generation of 3D scenes. Our model generalizes previous works that focus on single objects by removing the assumption that the camera pose distribution can be shared across samples. We show that GAUDI obtains state-of-the-art performance in the unconditional generative setting across multiple datasets and allows for conditional generation of 3D scenes given conditioning variables like sparse image observations or text that describes the scene.
RobbinDeBank t1_iv74pcy wrote
Seems like we will see Apple VR headset coming soon
Mefaso t1_iv9eshj wrote
Apple publishing research?
bakochba t1_iv8jfyq wrote
I wonder how much memory and time it takes to train models like this
nemesit t1_ivbgb8e wrote
Sounds great for games with destructive environment where interiors for buildings could just be ai generated when needed
ID4gotten t1_iv77qkz wrote
I can't wait to visit the beigeverse