BlockNeRF

• Block-NeRF: Scalable Large Scene Neural View Synthesis
• variant of Neural Radiance Field
• reconstruct large-scale environments
• scaling NeRF to render city-scale scenes spanning multiple blocks, it is vital to decompose the scene into individually trained NeRFs that can be optimized independently.
• this decomposition decouples rendering time from scene size
• allows per-block updates of the environment
• data collected will necessarily have transient objects and variations in appearance
• modifying the underlying NeRF architecture to make NeRF robust to data captured over months under different environmental conditions
• appearance Embedding, learned pose refinement, and controllable exposure to each individual NeRF
• procedure for aligning appearance between adjacent NeRFs so that they can be seamlessly combined
• building an entire neighborhood in San Francisco from 2.8M images using a grid of Block-NeRFs, forming the largest neural scene representation to date