Excited to share that MinD-Vis has been accepted by CVPR23. 🥳 TL;DR: We use a two-stage model (self-supervised learning + latent diffusion model) to generate nature images from brain recordings. Check out our project page: mind-vis.github.io

Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity propose Mind-Video that learns spatiotemporal information from continuous fMRI data of the cerebral cortex progressively through masked brain modeling, multimodal contrastive learning with spatiotemporal

🧠✨ Our paper on "MindReading", aka fMRI to image reconstruction, is up this afternoon! Swing by our poster at #CVPR2023 #CVPR2026 to delve into the magic of brain decoding. 📍 Location: West Exhibit Hall #201 ⏰ Time: 04:30 PM - 06:30 PM Thu Project page: mind-vis.github.io

🧠✨Super excited to share that our work Mind-Video has been accepted by #NeurIPS2023 as an Oral presentation! 📍 Catch us live in New Orleans! TL; DR: We've cracked the code to decode photorealistic videos straight from human brain recordings! 📽️➡️🧠 NeurIPS Conference #AI4Science

Attending #NeurIPS2023 ? Come and check our paper which reconstructs high resolution viewed images from human brain activities! Our work significantly outperform previous SOTA in decoding accuracy by 39.34%. ID is 431! #NeuroAI #BCI #NeurIPS

Human NeRFs have shown incredible abilities rendering 3D avatar from single monocular videos. But can they train on videos with occlusions? I’m excited to share our new paper “Wild2Avatar: Rendering Humans Behind Occlusions”🧵 📖arxiv.org/pdf/2401.00431… 🌐cs.stanford.edu/~xtiange/proje…

🗣️Call for papers🗣️ ✨the 2nd GenAI4Health Workshop NeurIPS Conference 🌐genai4health.github.io Join us at NeurIPS2025 for the coolest intersection between generative AI (today’s most exciting technology) and human health (our most vital priority)! 👉🧵