119 citations · 390 across the 17 of their papers we have counts for
17 papers
Federated Graph Semantic and Structural Learning
Wenke Huang, Guancheng Wan, Mang Ye +1
Federated graph learning collaboratively learns a global graph neural network with distributed graphs, where the non-independent and identically distributed property is one of the…
Rotation Invariant Transformer for Recognizing Object in UAVs
Shuoyi Chen, Mang Ye, Bo Du
Recognizing a target of interest from the UAVs is much more challenging than the existing object re-identification tasks across multiple city cameras. The images taken by the UAVs…
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning
Wenke Huang, Mang Ye, Zekun Shi +1
Federated learning is an important privacy-preserving multi-party learning paradigm, involving collaborative learning with others and local updating on private data. Model heteroge…
An Empirical Study of CLIP for Text-based Person Search
Min Cao, Yang Bai, Ziyin Zeng +2
Text-based Person Search (TBPS) aims to retrieve the person images using natural language descriptions. Recently, Contrastive Language Image Pretraining (CLIP), a universal large c…
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
Mang Ye, Xiuwen Fang, Bo Du +2
Federated learning (FL) has drawn increasing attention owing to its potential use in large-scale industrial applications. Existing federated learning works mainly focus on model ho…
Symmetric Uncertainty-Aware Feature Transmission for Depth Super-Resolution
Wuxuan Shi, Mang Ye, Bo Du
Color-guided depth super-resolution (DSR) is an encouraging paradigm that enhances a low-resolution (LR) depth map guided by an extra high-resolution (HR) RGB image from the same s…
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
Ding Jiang, Mang Ye
Text-to-image person retrieval aims to identify the target person based on a given textual description query. The primary challenge is to learn the mapping of visual and textual mo…
Refined Semantic Enhancement towards Frequency Diffusion for Video Captioning
Xian Zhong, Zipeng Li, Shuqin Chen +3
Video captioning aims to generate natural language sentences that describe the given video accurately. Existing methods obtain favorable generation by exploring richer visual repre…
Learnable Privacy-Preserving Anonymization for Pedestrian Images
Junwu Zhang, Mang Ye, Yao Yang
This paper studies a novel privacy-preserving anonymization problem for pedestrian images, which preserves personal identity information (PII) for authorized models and prevents PI…
AVA-AVD: Audio-Visual Speaker Diarization in the Wild
Eric Zhongcong Xu, Zeyang Song, Satoshi Tsutsui +3
Audio-visual speaker diarization aims at detecting "who spoke when" using both auditory and visual signals. Existing audio-visual diarization datasets are mainly focused on indoor…
The Multi-Modal Video Reasoning and Analyzing Competition
Haoran Peng, He Huang, Li Xu +15
In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021. This competition is composed of four differen…
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval
Yongbiao Chen, Sheng Zhang, Fangxin Liu +3
Deep hamming hashing has gained growing popularity in approximate nearest neighbour search for large-scale image retrieval. Until now, the deep hashing for the image retrieval comm…
Multi-Scale Cascading Network with Compact Feature Learning for RGB-Infrared Person Re-Identification
Can Zhang, Hong Liu, Wei Guo +1
RGB-Infrared person re-identification (RGB-IR Re-ID) aims to match persons from heterogeneous images captured by visible and thermal cameras, which is of great significance in the…
Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification
Mang Ye, Jianbing Shen, David J. Crandall +2
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Due to the large intra-class variations and cross-modality discrep…
Deep Learning for Person Re-identification: A Survey and Outlook
Mang Ye, Jianbing Shen, Gaojie Lin +3
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand…
Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
Mang Ye, Xu Zhang, Pong C. Yuen +1
This paper studies the unsupervised embedding learning problem, which requires an effective similarity measurement between samples in low-dimensional embedding space. Motivated by…
Dynamic Label Graph Matching for Unsupervised Video Re-Identification
Mang Ye, Andy J Ma, Liang Zheng +2
Label estimation is an important component in an unsupervised person re-identification (re-ID) system. This paper focuses on cross-camera label estimation, which can be subsequentl…