Shuo Ni — accepted AI-conference papers

2026

UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes

Shuo Ni, Di Wang, He Chen, Haonan Guo, Ning Zhang, Jing Zhang

CVPR 2026

Instruction-driven segmentation in remote sensing generates masks from guidance, offering great potential for accessible and generalizable applications. However, existing methods suffer from fragmented task formulations and limited instruction data, hindering effective understanding and generalizati

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2023

CLR: Channel-wise Lightweight Reprogramming for Continual Learning

Yunhao Ge, Yuecheng Li, Shuo Ni, Jiaping Zhao, Ming-Hsuan Yang, Laurent Itti

ICCV 2023poster

Continual learning aims to emulate the human ability to continually accumulate knowledge over sequential tasks. The main challenge is to maintain performance on previously learned tasks after learning new tasks, i.e., to avoid catastrophic forgetting. We propose a Channel-wise Lightweight Reprogramm…

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