3 papers
cs.CV2026
EdMCGS: Event-Driven Markov Chain Gaussian Splatting for Extreme-Low-Frame-Rate Dynamic Scene Reconstruction
Yuzhong Wang, Wenmin Wang, Xinxing Yu
We present EdMCGS (Event-driven Markov chain Gaussian Splatting), an end-to-end method for reconstructing dynamic 3D scenes from extreme-low-frame-rate RGB together with an event s…
cs.CV2026
FMRFusion: Frequency-Aware Multi-View Representation Learning for Heterogeneous Image Fusion
Tao Zhoua, Yunlong Liu, Qinghui Chen +6
Infrared and visible image fusion aims to generate a composite image that retains significant target information and preserves detailed textures, integrating two heterogeneous moda…
cs.CV2026
Distilled Large Language Model-Driven Dynamic Sparse Expert Activation Mechanism
Qinghui Chen, Zekai Zhang, Zaigui Zhang +5
High inter-class similarity, extreme scale variation, and limited computational budgets hinder reliable visual recognition across diverse real-world data. Existing vision-centric a…