We present Thera🔥: The new SOTA arbitrary-scale super-resolution method with built-in anti-aliasing. Our approach introduces Neural Heat Fields, which guarantee exact Gaussian filtering at any scale, enabling continuous image reconstruction without extra computational cost.
Researchers at @ETH_en have developed an AI-based solution that uses #satellite images to measure snow depth with a much better resolution than previous methods. Good news for me as a touring skier⛷️❄️🏔️! https://t.co/5quzaeTwTm
AI + Satellites = accurate measurement of snow . 🛰❄
This provides winter sport enthusiasts or operators of hydropower plants with an indication of how certain they can be about the estimate of #SnowDepth across Switzerland.
https://t.co/syHTFUtFKn
@innosuisse @WSL_research
Introducing Marigold 🌼 - a universal monocular depth estimator, delivering incredibly sharp predictions in the wild! Based on Stable Diffusion, it is trained with synthetic depth data only and excels in zero-shot adaptation to real-world imagery. Check it out:
🌐 Website: https://t.co/rBXhxQChn4
🤗 Hugging Face Space: https://t.co/CYvZZQtEYr
📄 Paper: https://t.co/eEw11yW6MY
👾 Code: https://t.co/0L49Znp2z1
The team: Bingxin Ke (@KBingxin), yours truly (@AntonObukhov1), Shengyu Huang (@ShengyHuang), Nando Metzger (@NandoMetzger), Rodrigo Caye Daudt (@rcdaudt), and Konrad Schindler.
#ComputerVision #PRS #ETHZurich
Excited to announce that our paper "Guided Depth Super-Resolution by Deep Anisotropic Diffusion" has been accepted at CVPR 2023!🎉 You can check out the ArXiv preprint and code repository to learn more about the research. #CVPR2023#SuperResolution
https://t.co/zd27I3lzVa