1 code implementation • CVPR 2023 • Zekun Zhang, Minh Hoai
This paper proposes a novel method to improve the performance of a trained object detector on scenes with fixed camera perspectives based on self-supervised adaptation.
no code implementations • 25 May 2019 • Zekun Zhang, Tianfu Wu
One scheme of learning attacks is to design a proper adversarial objective function that leads to the imperceptible perturbation for any test image (e. g., the Carlini-Wagner (C&W) method).
4 code implementations • ACL 2018 • Guokan Shang, Wensi Ding, Zekun Zhang, Antoine Jean-Pierre Tixier, Polykarpos Meladianos, Michalis Vazirgiannis, Jean-Pierre Lorré
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
Ranked #1 on Meeting Summarization on ICSI Meeting Corpus
Abstractive Dialogue Summarization Abstractive Text Summarization +6