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20172026
most citedAttributes Guided Feature Learning for Vehicle Re-identification

34 citations · 88 across the 21 of their papers we have counts for

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22 papers · 1 filter

cs.CV2026

DCG ReID: Disentangling Collaboration and Guidance Fusion Representations for Multi-modal Vehicle Re-Identification

Aihua Zheng, Ya Gao, Shihao Li +2

Multi-modal vehicle Re-Identification (ReID) aims to leverage complementary information from RGB, Near Infrared (NIR), and Thermal Infrared (TIR) modalities to retrieve the same ve…

cs.CV2025

UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification

Xixi Wan, Aihua Zheng, Bo Jiang +3

Multi-modal object Re-IDentification (ReID) has gained considerable attention with the goal of retrieving specific targets across cameras using heterogeneous visual data sources. A…

cs.CV2025

ICPL-ReID: Identity-Conditional Prompt Learning for Multi-Spectral Object Re-Identification

Shihao Li, Chenglong Li, Aihua Zheng +2

Multi-spectral object re-identification (ReID) brings a new perception perspective for smart city and intelligent transportation applications, effectively addressing challenges fro…

cs.CV2025

Collaborative Enhancement Network for Low-quality Multi-spectral Vehicle Re-identification

Aihua Zheng, Yongqi Sun, Zi Wang +2

The performance of multi-spectral vehicle Re-identification (ReID) is significantly degraded when some important discriminative cues in visible, near infrared and thermal infrared…

cs.CV2025★ 1 cited

Reliable Multi-Modal Object Re-Identification via Modality-Aware Graph Reasoning

Xixi Wan, Aihua Zheng, Zi Wang +3

Multi-modal data provides abundant and diverse object information, crucial for effective modal interactions in Re-Identification (ReID) tasks. However, existing approaches often ov…

cs.CV2023

Multi-query Vehicle Re-identification: Viewpoint-conditioned Network, Unified Dataset and New Metric

Aihua Zheng, Chaobin Zhang, Weijun Zhang +4

Existing vehicle re-identification methods mainly rely on the single query, which has limited information for vehicle representation and thus significantly hinders the performance…

cs.CV2023★ 1 cited

Dynamic Enhancement Network for Partial Multi-modality Person Re-identification

Aihua Zheng, Ziling He, Zi Wang +2

Many existing multi-modality studies are based on the assumption of modality integrity. However, the problem of missing arbitrary modalities is very common in real life, and this p…

cs.CV2023

Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification

Aihua Zheng, Zhiqi Ma, Zi Wang +1

Multi-spectral vehicle re-identification aims to address the challenge of identifying vehicles in complex lighting conditions by incorporating complementary visible and infrared in…

cs.CV2023★ 1 cited

MODIFY: Model-driven Face Stylization without Style Images

Yuhe Ding, Jian Liang, Jie Cao +2

Existing face stylization methods always acquire the presence of the target (style) domain during the translation process, which violates privacy regulations and limits their appli…

cs.CV2023

MAPS: A Noise-Robust Progressive Learning Approach for Source-Free Domain Adaptive Keypoint Detection

Yuhe Ding, Jian Liang, Bo Jiang +2

Existing cross-domain keypoint detection methods always require accessing the source data during adaptation, which may violate the data privacy law and pose serious security concer…

cs.CV2022★ 4 cited

Parallel Augmentation and Dual Enhancement for Occluded Person Re-identification

Zi Wang, Huaibo Huang, Aihua Zheng +2

Occluded person re-identification (Re-ID), the task of searching for the same person's images in occluded environments, has attracted lots of attention in the past decades. Recent…

cs.CV2022★ 2 cited

Multi-spectral Vehicle Re-identification with Cross-directional Consistency Network and a High-quality Benchmark

Aihua Zheng, Xianpeng Zhu, Zhiqi Ma +3

To tackle the challenge of vehicle re-identification (Re-ID) in complex lighting environments and diverse scenes, multi-spectral sources like visible and infrared information are t…

cs.CV2022

Disentangled Generation Network for Enlarged License Plate Recognition and A Unified Dataset

Chenglong Li, Xiaobin Yang, Guohao Wang +4

License plate recognition plays a critical role in many practical applications, but license plates of large vehicles are difficult to be recognized due to the factors of low resolu…

cs.CV2022★ 6 cited

ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation

Yuhe Ding, Lijun Sheng, Jian Liang +2

Unsupervised domain adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target domain. Owing to privacy concerns and heavy data transmission, s…

cs.CV2020★ 4 cited

Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification

Aihua Zheng, Xia Sun, Chenglong Li +1

Vehicle re-identification (Re-ID) is an active task due to its importance in large-scale intelligent monitoring in smart cities. Despite the rapid progress in recent years, most ex…

cs.CV2020

Unsupervised Contrastive Photo-to-Caricature Translation based on Auto-distortion

Yuhe Ding, Xin Ma, Mandi Luo +2

Photo-to-caricature translation aims to synthesize the caricature as a rendered image exaggerating the features through sketching, pencil strokes, or other artistic drawings. Style…

cs.CV2020★ 1 cited

Lets Play Music: Audio-driven Performance Video Generation

Hao Zhu, Yi Li, Feixia Zhu +2

We propose a new task named Audio-driven Per-formance Video Generation (APVG), which aims to synthesizethe video of a person playing a certain instrument guided bya given music aud…

cs.CV2020★ 2 cited

STADB: A Self-Thresholding Attention Guided ADB Network for Person Re-identification

Bo Jiang, Sheng Wang, Xiao Wang +1

Recently, Batch DropBlock network (BDB) has demonstrated its effectiveness on person image representation and re-identification task via feature erasing. However, BDB drops the fea…

cs.CV2020★ 16 cited

Deep Audio-Visual Learning: A Survey

Hao Zhu, Mandi Luo, Rui Wang +2

Audio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfull…

cs.CV2019

Multi-Adapter RGBT Tracking

Chenglong Li, Andong Lu, Aihua Zheng +2

The task of RGBT tracking aims to take the complementary advantages from visible spectrum and thermal infrared data to achieve robust visual tracking, and receives more and more at…

cs.CV2019★ 34 cited

Attributes Guided Feature Learning for Vehicle Re-identification

Hongchao Li, Xianmin Lin, Aihua Zheng +4

Vehicle Re-ID has recently attracted enthusiastic attention due to its potential applications in smart city and urban surveillance. However, it suffers from large intra-class varia…

cs.CV2017★ 16 cited

A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel Approach

Chenglong Li, Guizhao Wang, Yunpeng Ma +3

Despite significant progress, image saliency detection still remains a challenging task in complex scenes and environments. Integrating multiple different but complementary cues, l…