activity
20242026
collaborators

5 papers

cs.CV2026

Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution

Jiangwei Mo, Xi Lu, Hanlin Wu

High-resolution remote sensing images (RSIs) are crucial for Earth observation applications, yet acquiring them is often limited by sensor constraints and costs. In recent years, g…

cs.CV2026

MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models

Ruiqi Wang, Qi Yu, Jie Ma +1

High-resolution (HR) land-cover mapping is often constrained by the high cost of dense HR annotations. We revisit this problem from the perspective of map super-resolution, which e…

cs.CV2026

Linearized Coupling Flow with Shortcut Constraints for One-Step Face Restoration

Xiaohui Sun, Hanlin Wu

Face restoration can be formulated as a continuous-time transformation between image distributions via Flow Matching (FM). However, standard FM typically employs independent coupli…

eess.IV2025

Single-Step Latent Consistency Model for Remote Sensing Image Super-Resolution

Xiaohui Sun, Jiangwei Mo, Hanlin Wu +1

Recent advancements in diffusion models (DMs) have greatly advanced remote sensing image super-resolution (RSISR). However, their iterative sampling processes often result in slow…

eess.IV2024

Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images

Hanlin Wu, Jiangwei Mo, Xiaohui Sun +1

Recent advancements in diffusion models have significantly improved performance in super-resolution (SR) tasks. However, previous research often overlooks the fundamental differenc…