439 citations · 798 across the 21 of their papers we have counts for
21 papers · 1 filter
Region Generation and Assessment Network for Occluded Person Re-Identification
Shuting He, Weihua Chen, Kai Wang +4
Person Re-identification (ReID) plays a more and more crucial role in recent years with a wide range of applications. Existing ReID methods are suffering from the challenges of mis…
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Jianyang Gu, Hao Luo, Kai Wang +3
Unsupervised domain adaptive person re-identification (Re-ID) methods alleviate the burden of data annotation through generating pseudo supervision messages. However, real-world Re…
Revisiting Vision Transformer from the View of Path Ensemble
Shuning Chang, Pichao Wang, Hao Luo +2
Vision Transformers (ViTs) are normally regarded as a stack of transformer layers. In this work, we propose a novel view of ViTs showing that they can be seen as ensemble networks…
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Weihua Chen, Xianzhe Xu, Jian Jia +5
Human-centric visual tasks have attracted increasing research attention due to their widespread applications. In this paper, we aim to learn a general human representation from mas…
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
Jianyang Gu, Kai Wang, Hao Luo +6
Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the r…
Exploring the Coordination of Frequency and Attention in Masked Image Modeling
Jie Gui, Tuo Chen, Minjing Dong +4
Recently, masked image modeling (MIM), which learns visual representations by reconstructing the masked patches of an image, has dominated self-supervised learning in computer visi…
MimCo: Masked Image Modeling Pre-training with Contrastive Teacher
Qiang Zhou, Chaohui Yu, Hao Luo +2
Recent masked image modeling (MIM) has received much attention in self-supervised learning (SSL), which requires the target model to recover the masked part of the input image. Alt…
Dynamic Gradient Reactivation for Backward Compatible Person Re-identification
Xiao Pan, Hao Luo, Weihua Chen +6
We study the backward compatible problem for person re-identification (Re-ID), which aims to constrain the features of an updated new model to be comparable with the existing featu…
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
Hao Luo, Pichao Wang, Yi Xu +5
Transformer-based supervised pre-training achieves great performance in person re-identification (ReID). However, due to the domain gap between ImageNet and ReID datasets, it usual…
Scaled ReLU Matters for Training Vision Transformers
Pichao Wang, Xue Wang, Hao Luo +5
Vision transformers (ViTs) have been an alternative design paradigm to convolutional neural networks (CNNs). However, the training of ViTs is much harder than CNNs, as it is sensit…
An Empirical Study of Vehicle Re-Identification on the AI City Challenge
Hao Luo, Weihua Chen, Xianzhe Xu +7
This paper introduces our solution for the Track2 in AI City Challenge 2021 (AICITY21). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones
Chong Liu, Yuqi Zhang, Hao Luo +6
Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions. This paper describes our solution to the Track 3…
Multi-modal Bifurcated Network for Depth Guided Image Relighting
Hao-Hsiang Yang, Wei-Ting Chen, Hao-Lun Luo +1
Image relighting aims to recalibrate the illumination setting in an image. In this paper, we propose a deep learning-based method called multi-modal bifurcated network (MBNet) for…
NTIRE 2021 Depth Guided Image Relighting Challenge
Majed El Helou, Ruofan Zhou, Sabine Susstrunk +1
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalizati…
TransReID: Transformer-based Object Re-Identification
Shuting He, Hao Luo, Pichao Wang +3
Extracting robust feature representation is one of the key challenges in object re-identification (ReID). Although convolution neural network (CNN)-based methods have achieved grea…
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification
Jianyang Gu, Hao Luo, Weihua Chen +6
This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap…
Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor
Wensheng Cheng, Hao Luo, Wen Yang +2
Lane marker extraction is a basic yet necessary task for autonomous driving. Although past years have witnessed major advances in lane marker extraction with deep learning models,…
Active Ensemble Deep Learning for Polarimetric Synthetic Aperture Radar Image Classification
Sheng-Jie Liu, Haowen Luo, Qian Shi
Although deep learning has achieved great success in image classification tasks, its performance is subject to the quantity and quality of training samples. For classification of p…
A Novel Self-Intersection Penalty Term for Statistical Body Shape Models and Its Applications in 3D Pose Estimation
Zaiqiang Wu, Wei Jiang, Hao Luo +1
Statistical body shape models are widely used in 3D pose estimation due to their low-dimensional parameters representation. However, it is difficult to avoid self-intersection betw…
AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
Xuan Zhang, Hao Luo, Xing Fan +6
In this paper, we propose a novel method called AlignedReID that extracts a global feature which is jointly learned with local features. Global feature learning benefits greatly fr…
Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification
Qiqi Xiao, Hao Luo, Chi Zhang
Person re-identification (ReID) is an important task in computer vision. Recently, deep learning with a metric learning loss has become a common framework for ReID. In this paper,…