12 DAILY ICCV Thursday Poster Presentation SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields Anh-Quan Cao is a thirdyear PhD student at Inria Paris, supervised by Raoul de Charette. His paper proposes a selfsupervised 3D reconstruction method from a single image. He speaks to us ahead of his poster this morning. In this paper, Anh-Quan extends the capabilities of 3D reconstruction to encompass large-scale scenes, such as outdoor driving scenarios and robot navigation, using only imagebased supervision. He builds on a NeRF-based method, using a sequence of future frames to supervise the training of the method conditioned on a single image. The idea follows his previous work, MonoScene, in which he successfully predicted complete 3D semantic scenes from a single image with 3D groundtruth. “The setting is very challenging because we want to work on a large-scale scene,” Anh-Quan explains. “It’s a very complex scene with a lot of occlusion, objects, and clutter because it’s 100 meters away. To reconstruct it from only a single image is hard. Furthermore, we don’t want to use 3D groundtruth; we only want to use images to supervise, adding another difficulty to the problem.”
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