no code implementations • 21 May 2022 • Ruili Feng, Jie Xiao, Kecheng Zheng, Deli Zhao, Jingren Zhou, Qibin Sun, Zheng-Jun Zha
Human can extrapolate well, generalize daily knowledge into unseen scenarios, raise and answer counterfactual questions.
no code implementations • 24 Mar 2022 • Kecheng Zheng, Yang Cao, Kai Zhu, Ruijing Zhao, Zheng-Jun Zha
However, its generalization performance to heterogeneous tasks is inferior to other architectures (e. g., CNNs and transformers) due to the extensive retention of domain information.
no code implementations • 3 Mar 2022 • Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha
In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers as a dynamically self-refining Gaussian process to alleviate the bias to unseen domain for improving the generalization.
Generalizable Person Re-identification
Representation Learning
no code implementations • 3 Mar 2022 • Zhipeng Huang, Jiawei Liu, Liang Li, Kecheng Zheng, Zheng-Jun Zha
RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images.
1 code implementation • 1 Dec 2021 • Zizheng Yang, Xin Jin, Kecheng Zheng, Feng Zhao
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
1 code implementation • 27 Nov 2021 • Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha
The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.
Domain Generalization
Generalizable Person Re-identification
3 code implementations • 11 Aug 2021 • Lingxiao He, Wu Liu, Jian Liang, Kecheng Zheng, Xingyu Liao, Peng Cheng, Tao Mei
Instead, we aim to explore multiple labeled datasets to learn generalized domain-invariant representations for person re-id, which is expected universally effective for each new-coming re-id scenario.
Generalizable Person Re-identification
Knowledge Distillation
no code implementations • 31 Jul 2021 • Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Jiawei Liu, Zhizheng Zhang, Zheng-Jun Zha
Occluded person re-identification (ReID) aims to match person images with occlusion.
no code implementations • 7 May 2021 • Jiawei Liu, Zhipeng Huang, Kecheng Zheng, Dong Liu, Xiaoyan Sun, Zheng-Jun Zha
It describes unseen target domain as a combination of the known source ones, and explicitly learns domain-specific representation with target distribution to improve the model's generalization by a meta-learning pipeline.
no code implementations • CVPR 2021 • Jiawei Liu, Zheng-Jun Zha, Wei Wu, Kecheng Zheng, Qibin Sun
The key factor for video person re-identification is to effectively exploit both spatial and temporal clues from video sequences.
no code implementations • 29 Mar 2021 • Rui Zhao, Kecheng Zheng, Zheng-Jun Zha, Hongtao Xie, Jiebo Luo
The cross-modal memory module is employed to record the instance embeddings of all the datasets for global negative mining.
1 code implementation • 29 Mar 2021 • Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.
no code implementations • 25 Mar 2021 • Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Quanzeng You, Zicheng Liu, Kecheng Zheng, Zhibo Chen
Each recomposed feature, obtained based on the domain-invariant feature (which enables a reliable inheritance of identity) and an enhancement from a domain specific feature (which enables the approximation of real distributions), is thus an "ideal" augmentation.
1 code implementation • CVPR 2021 • Kecheng Zheng, Wu Liu, Lingxiao He, Tao Mei, Jiebo Luo, Zheng-Jun Zha
In this paper, we propose a Group-aware Label Transfer (GLT) algorithm, which enables the online interaction and mutual promotion of pseudo-label prediction and representation learning.
Domain Adaptive Person Re-Identification
Online Clustering
+2
1 code implementation • 16 Dec 2020 • Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zheng-Jun Zha
Based on this finding, we propose to exploit the uncertainty (measured by consistency levels) to evaluate the reliability of the pseudo-label of a sample and incorporate the uncertainty to re-weight its contribution within various ReID losses, including the identity (ID) classification loss per sample, the triplet loss, and the contrastive loss.
Domain Adaptive Person Re-Identification
Person Re-Identification
+1
no code implementations • 10 Oct 2020 • Kecheng Zheng, Wu Liu, Jiawei Liu, Zheng-Jun Zha, Tao Mei
This hard selection strategy is able to fuse the strong-relevant multi-modality features for alleviating the problem of matching redundancy.
Ranked #6 on
Text based Person Retrieval
on CUHK-PEDES
no code implementations • 10 Apr 2020 • Rui Zhao, Kecheng Zheng, Zheng-Jun Zha
Existing dominant approaches for cross-modal video-text retrieval task are to learn a joint embedding space to measure the cross-modal similarity.
1 code implementation • NeurIPS 2019 • Kecheng Zheng, Zheng-Jun Zha, Wei Wei
Abstraction reasoning is a long-standing challenge in artificial intelligence.