no code implementations • 29 Dec 2024 • Daiheng Gao, Shilin Lu, Shaw Walters, Wenbo Zhou, Jiaming Chu, Jie Zhang, Bang Zhang, Mengxi Jia, Jian Zhao, Zhaoxin Fan, Weiming Zhang
Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge.
no code implementations • 7 Sep 2024 • Lingzhe Zhang, Tong Jia, Kangjin Wang, Mengxi Jia, Yang Yong, Ying Li
Experimental outcomes highlight LogCleaner's capability to reduce over 70% of log events in anomaly detection, accelerating the model's inference speed by approximately 300%, and universally improving the performance of models for anomaly detection.
no code implementations • 8 Jun 2023 • Yunpeng Zhai, Peixi Peng, Mengxi Jia, Shiyong Li, Weiqiang Chen, Xuesong Gao, Yonghong Tian
Extensive experiments demonstrate that (1) CRS approximately measures the performance of models without labeled samples; (2) and PEG produces new state-of-the-art accuracy for person re-identification, indicating the great potential of population-based network cooperative training for unsupervised learning.
no code implementations • CVPR 2023 • Xinhua Cheng, Yanmin Wu, Mengxi Jia, Qian Wang, Jian Zhang
In this work, we attempt to learn an object-compositional neural implicit representation for editable scene rendering by leveraging labels inferred from the off-the-shelf 2D panoptic segmentation networks instead of the ground truth annotations.
no code implementations • 6 Jul 2021 • Mengxi Jia, Xinhua Cheng, Shijian Lu, Jian Zhang
To better eliminate interference from occlusions, we design a contrast feature learning technique (CFL) for better separation of occlusion features and discriminative ID features.
2 code implementations • ECCV 2020 • Yunpeng Zhai, Qixiang Ye, Shijian Lu, Mengxi Jia, Rongrong Ji, Yonghong Tian
Often the best performing deep neural models are ensembles of multiple base-level networks, nevertheless, ensemble learning with respect to domain adaptive person re-ID remains unexplored.
Domain Adaptive Person Re-Identification
Ensemble Learning
+1
no code implementations • 3 Jul 2020 • Mengxi Jia, Yunpeng Zhai, Shijian Lu, Siwei Ma, Jian Zhang
RGB-Infrared (IR) cross-modality person re-identification (re-ID), which aims to search an IR image in RGB gallery or vice versa, is a challenging task due to the large discrepancy between IR and RGB modalities.
Cross-Modality Person Re-identification
Person Re-Identification