3 papers
cs.AI2026
CryoACE: An Atom-centric Framework for Accurate and Automated Model Building in Cryo-EM
Minzhang Li, Mingrui Li, Weichen Qin +5
Protein automodeling from cryo-EM density maps faces unique challenges in enforcing physicochemical validity and managing conformational heterogeneity. Current solvers are often li…
cs.CV2025
CryoFastAR: Fast Cryo-EM Ab Initio Reconstruction Made Easy
Jiakai Zhang, Shouchen Zhou, Haizhao Dai +5
Pose estimation from unordered images is fundamental for 3D reconstruction, robotics, and scientific imaging. Recent geometric foundation models, such as DUSt3R, enable end-to-end…
cs.CV2024
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM
Yingjun Shen, Haizhao Dai, Qihe Chen +4
Foundation models in computer vision have demonstrated exceptional performance in zero-shot and few-shot tasks by extracting multi-purpose features from large-scale datasets throug…