🌍 Earth Science

🎞️ ECCV2026 · 4 paper notes

📌 Same area in other venues: 📷 CVPR2026 (2) · 🔬 ICLR2026 (7) · 🧪 ICML2026 (2) · 🤖 AAAI2026 (2) · 🧠 NeurIPS2025 (6) · 📷 CVPR2025 (1)

🔥 Top topics: Time-Series Forecasting ×2

Lessons and Open Questions from a Unified Study of Camera-Trap Species Recognition Over Time

The paper reframes camera-trap species recognition from cross-site generalization to streaming evaluation at a fixed site over time, builds StreamTrap (17 datasets, 546 camera traps), and answers four deployment questions — showing that naive accumulated fine-tuning can fall below zero-shot, offering a LoRA + Balanced Softmax recipe with post-processing, and laying out a list of open questions.

Mapping Dark-Matter Clusters via Physics-Guided Diffusion Models

The paper releases DARKCLUSTERS-15K, the largest galaxy-cluster mass-mapping dataset to date (15,000 paired surface-mass-density maps and simulated three-band HST photometry), trains a photometry-conditioned diffusion prior on it, and turns strong- and weak-lensing physics into likelihood guidance terms driven by DAPS annealing posterior sampling — producing 512×512 non-parametric mass maps with calibrated per-pixel uncertainties in minutes, beating Kaiser-Squires, Napier et al. and a UNet baseline on the TNG/SIMBA held-out test sets and approaching expert-tuned reconstructions on the real cluster MACS 1206.

RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs

RainODE learns continuous precipitation trajectories with a discrete-teacher-guided latent Neural ODE and refines intensity and detail through a Brownian Bridge, supporting unseen temporal queries while raising RAPID-60min CSI-M from SimVP's 0.141 to 0.220, without guaranteeing a corresponding reduction in pixel-wise error.

Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction

Addressing the heavy intermediate redundancy and memory bottlenecks of uniform token computation in ViT-based meteorological forecasting, Sparse-Reslim proposes a parameter-free sparse residual routing module that routes only 25% of spatial tokens through expensive middle blocks and scatters the residual delta back, achieving ~2.5× training speedup, over 2.2× peak VRAM reduction, and superior forecast skill across all variables.