no code implementations • 6 Jan 2024 • Zhenan Fan, Bissan Ghaddar, Xinglu Wang, Linzi Xing, Yong Zhang, Zirui Zhou
The rapid advancement of artificial intelligence (AI) techniques has opened up new opportunities to revolutionize various fields, including operations research (OR).
1 code implementation • ICCV 2023 • Mohsen Gholami, Mohammad Akbari, Xinglu Wang, Behnam Kamranian, Yong Zhang
This is the first work that proposes transferability estimation for object detection task.
Ranked #1 on Transferability on classification benchmark
no code implementations • 26 May 2022 • Chengyu Qiao, Zhiyu Xiang, Xinglu Wang
Visual relocalization aims to estimate the pose of a camera from one or more images.
no code implementations • IEEE International Conference on Image Processing (ICIP) 2021 • Shengxiong Ouyang, Xinglu Wang, Kejie Lyu, Yingming Li
Cross domain weakly supervised object detection (CDWSOD), where we can get access to instance-level annotations in the source domain while only image-level annotations are available in the target domain, adapts object detectors from label-rich to label-poor domains.
no code implementations • 28 Dec 2020 • Xinglu Wang
The key to accurately measure visual similarities is learning discriminative features, which not only captures clues from different spatial scales, but also jointly inferences on multiple scales, with the ability to determine reliability and ID-relativity of each clue.
no code implementations • 28 Dec 2020 • Xinglu Wang
In this paper, we propose to address this problem with a new deep metric learning method called Adversarial Triplet Embedding (ATE), in which we simultaneously generate adversarial triplets and discriminative feature embedding in an unified framework.