Xiankang He — accepted AI-conference papers

2026

GeoMotion: Rethinking Motion Segmentation via Latent 4D Geometry

Xiankang He, Peile Lin, Ying Cui, Dongyan Guo, Chunhua Shen, Xiaoqin Zhang

CVPR 2026

Motion segmentation in dynamic scenes is highly challenging, as conventional methods heavily rely on estimating camera poses and point correspondences from inherently noisy motion cues. Existing statistical inference or iterative optimization techniques that struggle to mitigate the cumulative error

Cited by 0 Source ↗code ↗Scholar ↗

2025

DiffCalib: Reformulating Monocular Camera Calibration as Diffusion-Based Dense Incident Map Generation

Xiankang He, Guangkai Xu, Bo Zhang, Hao Chen, Ying Cui, Dongyan Guo

AAAI 2025technical

Monocular camera calibration is a key precondition for numerous 3D vision applications. Despite considerable advancements, existing methods often hinge on specific assumptions and struggle to generalize across varied real-world scenarios, and the performance is limited by insufficient training data.…

Cited by 4 Source ↗PDF ↗Scholar ↗