Jiajun Le — accepted AI-conference papers

2026

GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry

AAAI 2026technical

Recent progress in two-view geometry increasingly emphasizes enforcing smoothness and global consistency priors when estimating motion fields between pairs of images. However, in complex real-world scenes, characterized by extreme viewpoint and scale changes as well as pronounced depth discontinuiti

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2025

DeMo: Deep Motion Field Consensus with Learnable Kernels for Two-view Correspondence Learning

Yifan Lu, Jiajun Le, Zizhuo Li, Yixuan Yuan, Jiayi Ma

AAAI 2025technical

As a long-range prior, motion consensus essentially forces the overall spatial transformation between a pair of images to be smooth and consistent, which is naturally well-suited for two-view correspondence learning. However, such precious property remains under-explored by most existing studies due…

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