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Lucidfusion: Generating 3d gaussians with arbitrary unposed images
Recent large reconstruction models have made notable progress in generating high-quality
3D objects from single images. However, these methods often struggle with controllability …
3D objects from single images. However, these methods often struggle with controllability …
SCARF: Scalable Continual Learning Framework for Memory‐efficient Multiple Neural Radiance Fields
Y Wang, J Wang, C Wang, W Duan… - Computer Graphics …, 2024 - Wiley Online Library
This paper introduces a novel continual learning framework for synthesising novel views of
multiple scenes, learning multiple 3D scenes incrementally, and updating the network …
multiple scenes, learning multiple 3D scenes incrementally, and updating the network …
-NeRF: Modeling Multiple Scenes via Conditional-cum-Continual Neural Radiance Fields
Neural radiance fields (NeRF) have exhibited highly photorealistic rendering of novel views
through per-scene optimization over a single 3D scene. With the growing popularity of NeRF …
through per-scene optimization over a single 3D scene. With the growing popularity of NeRF …