Junchen Ge — accepted AI-conference papers

2026

IGen: Scalable Data Generation for Robot Learning from Open-World Images

Chenghao Gu, Haolan Kang, Junchao Lin, Jinghe Wang, Duo Wu, Shuzhao Xie +7

CVPR 2026

The rise of generalist robotic policies has created an exponential demand for large-scale training data. However, on-robot data collection is labor-intensive and often limited to specific environments. In contrast, open-world images capture a vast diversity of real-world scenes that naturally align

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2025

Image Stitching in Adverse Condition: A Bidirectional-Consistency Learning Framework and Benchmark

Zengxi Zhang, Junchen Ge, Zhiying Jiang, Miao Zhang, Jinyuan Liu

NeurIPS 2025poster

Deep learning-based image stitching methods have achieved promising performance on conventional stitching datasets. However, real-world scenarios may introduce challenges such as complex weather conditions, illumination variations, and dynamic scene motion, which severely degrade image quality and l…

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