Planetary Feature Fields are Scalable Earth Representations

arXiv:2609.37784 · cs.CV, cs.LG · Submitted 2026-09-29 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Embeddings — 50× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• CVF International Conference on Computer Vision — 7× in this paper
• Continual Learning — 6× in this paper · explained in 2 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 6× in this paper
• Adaptation — 5× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• In European Conference on Computer Vision — 4× in this paper
• Adam — 3× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 3× in this paper · explained in 5 episodes
• Fields of the World — 3× in this paper
• Regularization — 3× in this paper · explained in 3 episodes
• Decode — 2× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 2× in this paper
• Redundancy — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Cooperation — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• International Joint Conference on Artificial Intelligence — 1× in this paper
• Intrinsic Dimension — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Linear probe — 1× in this paper · explained in 2 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Spatial Functa: Scaling Functa to ImageNet Classification and Generation
• AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data
• MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale
• TerraCodec: Compressing Optical Earth Observation Data
• Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space
• SLED: Scalable Location Encoding via Distillation
• CD-NGP: A Fast Scalable Continual Representation for Dynamic Scenes
• Lightweight, Pre-trained Transformers for Remote Sensing Timeseries
• Better Together: Evaluating the Complementarity of Earth Embedding Models

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