Reproduce “WP-CrackNet: A Collaborative Adversarial Learning Framework for End-to-End Weakly-Supervised Road Crack Detection” on OpenResearch

Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.

Universal app for Apple silicon and Intel. Requires macOS 11 or later.

About this paper

Nachuan Ma, Zhengfei Song, Qiang Hu, Xiaoyu Tang, Chengxi Zhang, Rui Fan, Lihua Xie

Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.