1 code implementation • 23 Dec 2024 • Wenxuan Fang, Junkai Fan, Yu Zheng, Jiangwei Weng, Ying Tai, Jun Li
Image dehazing, particularly with learning-based methods, has gained significant attention due to its importance in real-world applications.
no code implementations • 8 Oct 2024 • Guoqing Zhang, Tianqi Liu, Wenxuan Fang, yuhui Zheng
To this end, we propose a novel vision transformer based random walk framework for group re-ID.
no code implementations • 4 Feb 2024 • Wenxuan Fang, Wei Du, Renchu He, Yang Tang, Yaochu Jin, Gary G. Yen
The presence of nonlinearity, integer constraints, and a large number of decision variables adds complexity to this problem, posing challenges for traditional and evolutionary algorithms.
no code implementations • 2 Jan 2024 • Wei Du, Wenxuan Fang, Chen Liang, Yang Tang, Yaochu Jin
The primary objective of the peak-detection stage is to identify peaks in the fitness landscape of the original optimization problem.
no code implementations • 8 May 2022 • Wenxuan Fang, Kai Zhang, Yoli Shavit, Wensen Feng
Our method learns local and global augmentation policies which will increase the training loss, while the image retrieval network is forced to learn more powerful features for discriminating increasingly difficult examples.