Search Results for author: Yunhong Wang

Found 85 papers, 36 papers with code

Understanding Heterophily for Graph Neural Networks

no code implementations17 Jan 2024 Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

Firstly, we show that by applying a GC operation, the separability gains are determined by two factors, i. e., the Euclidean distance of the neighborhood distributions and $\sqrt{\mathbb{E}\left[\operatorname{deg}\right]}$, where $\mathbb{E}\left[\operatorname{deg}\right]$ is the averaged node degree.

Generic Knowledge Boosted Pre-training For Remote Sensing Images

1 code implementation9 Jan 2024 Ziyue Huang, Mingming Zhang, Yuan Gong, Qingjie Liu, Yunhong Wang

Deep learning models are essential for scene classification, change detection, land cover segmentation, and other remote sensing image understanding tasks.

Change Detection General Knowledge +4

DUA-DA: Distillation-based Unbiased Alignment for Domain Adaptive Object Detection

no code implementations17 Nov 2023 Yongchao Feng, Shiwei Li, Yingjie Gao, Ziyue Huang, Yanan Zhang, Qingjie Liu, Yunhong Wang

Though feature-alignment based Domain Adaptive Object Detection (DAOD) have achieved remarkable progress, they ignore the source bias issue, i. e. the aligned features are more favorable towards the source domain, leading to a sub-optimal adaptation.

Classification object-detection +2

ActiveDC: Distribution Calibration for Active Finetuning

no code implementations13 Nov 2023 Wenshuai Xu, Zhenghui Hu, Yu Lu, Jinzhou Meng, Qingjie Liu, Yunhong Wang

Firstly, we select samples for annotation by optimizing the distribution similarity between the subset to be selected and the entire unlabeled pool in continuous space.

Image Classification

Learning Historical Status Prompt for Accurate and Robust Visual Tracking

no code implementations3 Nov 2023 Wenrui Cai, Qingjie Liu, Yunhong Wang

To address this issue, we propose a Historical Information Prompter (HIP) to enhance the provision of historical information.

Visual Tracking

Improving Multi-Person Pose Tracking with A Confidence Network

no code implementations29 Oct 2023 Zehua Fu, Wenhang Zuo, Zhenghui Hu, Qingjie Liu, Yunhong Wang

Specifically, the keypoint confidence network is designed to determine whether each keypoint is occluded, and it is incorporated into the pose estimation module.

Human Detection Pose Estimation +1

Incremental Object Detection with CLIP

no code implementations13 Oct 2023 Yupeng He, Ziyue Huang, Qingjie Liu, Yunhong Wang

In the incremental detection task, unlike the incremental classification task, data ambiguity exists due to the possibility of an image having different labeled bounding boxes in multiple continuous learning stages.

Incremental Learning Object +2

Context-Enhanced Detector For Building Detection From Remote Sensing Images

no code implementations11 Oct 2023 Ziyue Huang, Mingming Zhang, Qingjie Liu, Wei Wang, Zhe Dong, Yunhong Wang

Our approach utilizes a three-stage cascade structure to enhance the extraction of contextual information and improve building detection accuracy.

Semantic Segmentation

CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding

no code implementations28 Sep 2023 Mingming Zhang, Qingjie Liu, Yunhong Wang

To address these problems, we propose a context-enhanced masked image modeling method (CtxMIM), a simple yet efficient MIM-based self-supervised learning for remote sensing image understanding.

Contrastive Learning Instance Segmentation +7

HiT: Building Mapping with Hierarchical Transformers

no code implementations18 Sep 2023 Mingming Zhang, Qingjie Liu, Yunhong Wang

The polygon head formulates a building polygon as serialized vertices with the bidirectional characteristic, a simple and elegant polygon representation avoiding the start or end vertex hypothesis.

Instance Segmentation Semantic Segmentation

Zero-Shot Scene Graph Generation via Triplet Calibration and Reduction

1 code implementation7 Sep 2023 Jiankai Li, Yunhong Wang, Weixin Li

In our framework, a triplet calibration loss is first presented to regularize the representations of diverse triplets and to simultaneously excavate the unseen triplets in incompletely annotated training scene graphs.

Graph Generation Scene Graph Generation

RFDforFin: Robust Deep Forgery Detection for GAN-generated Fingerprint Images

no code implementations18 Aug 2023 Hui Miao, Yuanfang Guo, Yunhong Wang

In this paper, we propose the first deep forgery detection approach for fingerprint images, which combines unique ridge features of fingerprint and generation artifacts of the GAN-generated images, to the best of our knowledge.

Binary Classification Image Generation

SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection

1 code implementation ICCV 2023 Jinqing Zhang, Yanan Zhang, Qingjie Liu, Yunhong Wang

In this paper, we propose Semantic-Aware BEV Pooling (SA-BEVPool), which can filter out background information according to the semantic segmentation of image features and transform image features into semantic-aware BEV features.

3D Object Detection

Common Knowledge Learning for Generating Transferable Adversarial Examples

no code implementations1 Jul 2023 Ruijie Yang, Yuanfang Guo, Junfu Wang, Jiantao Zhou, Yunhong Wang

Specifically, to reduce the model-specific features and obtain better output distributions, we construct a multi-teacher framework, where the knowledge is distilled from different teacher architectures into one student network.

Denoising Diffusion Autoencoders are Unified Self-supervised Learners

1 code implementation ICCV 2023 Weilai Xiang, Hongyu Yang, Di Huang, Yunhong Wang

Inspired by recent advances in diffusion models, which are reminiscent of denoising autoencoders, we investigate whether they can acquire discriminative representations for classification via generative pre-training.

Contrastive Learning Denoising +3

Heterophily-Aware Graph Attention Network

no code implementations7 Feb 2023 Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

In this paper, we firstly propose a heterophily-aware attention scheme and reveal the benefits of modeling the edge heterophily, i. e., if a GNN assigns different weights to edges according to different heterophilic types, it can learn effective local attention patterns, which enable nodes to acquire appropriate information from distinct neighbors.

Graph Attention Graph Representation Learning +1

An Empirical Study on Multi-Domain Robust Semantic Segmentation

no code implementations8 Dec 2022 Yajie Liu, Pu Ge, Qingjie Liu, Shichao Fan, Yunhong Wang

How to effectively leverage the plentiful existing datasets to train a robust and high-performance model is of great significance for many practical applications.

Data Augmentation Segmentation +1

Binary Graph Convolutional Network with Capacity Exploration

1 code implementation24 Oct 2022 Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

The current success of Graph Neural Networks (GNNs) usually relies on loading the entire attributed graph for processing, which may not be satisfied with limited memory resources, especially when the attributed graph is large.

Binarization Node Classification

Exploring Effective Knowledge Transfer for Few-shot Object Detection

1 code implementation5 Oct 2022 Zhiyuan Zhao, Qingjie Liu, Yunhong Wang

For the high-shot regime, we propose to use the knowledge learned from ImageNet as guidance for the feature learning in the fine-tuning stage, which will implicitly align the distributions of the novel classes.

Few-Shot Object Detection Object +2

D$^{\bf{3}}$: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos

1 code implementation25 Sep 2022 Rui He, Zehua Fu, Qingjie Liu, Yunhong Wang, Xunxun Chen

In this paper, the duplicate detection is newly and precisely defined as occlusion misreporting on the same athlete by multiple detection boxes in one frame.

Multi-Object Tracking

Enabling Homogeneous GNNs to Handle Heterogeneous Graphs via Relation Embedding

no code implementations23 Sep 2022 Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang

Extensive experiments demonstrate that our RE-GNN can effectively and efficiently handle the heterogeneous graphs and can be applied to various homogeneous GNNs.

Graph Learning Node Classification +1

SparseTT: Visual Tracking with Sparse Transformers

1 code implementation8 May 2022 Zhihong Fu, Zehua Fu, Qingjie Liu, Wenrui Cai, Yunhong Wang

In this paper, we relieve this issue with a sparse attention mechanism by focusing the most relevant information in the search regions, which enables a much accurate tracking.

Visual Tracking

PanFormer: a Transformer Based Model for Pan-sharpening

1 code implementation6 Mar 2022 Huanyu Zhou, Qingjie Liu, Yunhong Wang

Pan-sharpening aims at producing a high-resolution (HR) multi-spectral (MS) image from a low-resolution (LR) multi-spectral (MS) image and its corresponding panchromatic (PAN) image acquired by a same satellite.

RealGait: Gait Recognition for Person Re-Identification

1 code implementation13 Jan 2022 Shaoxiong Zhang, Yunhong Wang, Tianrui Chai, Annan Li, Anil K. Jain

Given that our experimental results show that current gait recognition approaches designed under data collected in controlled scenarios are inappropriate for real surveillance scenarios, we propose a novel gait recognition method, called RealGait.

Gait Recognition Person Recognition +1

Segmentation-Reconstruction-Guided Facial Image De-occlusion

no code implementations15 Dec 2021 Xiangnan Yin, Di Huang, Zehua Fu, Yunhong Wang, Liming Chen

The proposed model consists of a 3D face reconstruction module, a face segmentation module, and an image generation module.

3D Face Reconstruction Image Generation

Will You Ever Become Popular? Learning to Predict Virality of Dance Clips

no code implementations6 Nov 2021 Jiahao Wang, Yunhong Wang, Nina Weng, Tianrui Chai, Annan Li, Faxi Zhang, Sansi Yu

Therefore, virality prediction from dance challenges is of great commercial value and has a wide range of applications, such as smart recommendation and popularity promotion.

Unsupervised Cycle-consistent Generative Adversarial Networks for Pan-sharpening

1 code implementation20 Sep 2021 Huanyu Zhou, Qingjie Liu, Dawei Weng, Yunhong Wang

Most of existing methods fall into the supervised learning framework in which they down-sample the multi-spectral (MS) and panchromatic (PAN) images and regard the original MS images as ground truths to form training samples.

iDARTS: Improving DARTS by Node Normalization and Decorrelation Discretization

no code implementations25 Aug 2021 Huiqun Wang, Ruijie Yang, Di Huang, Yunhong Wang

Differentiable ARchiTecture Search (DARTS) uses a continuous relaxation of network representation and dramatically accelerates Neural Architecture Search (NAS) by almost thousands of times in GPU-day.

Neural Architecture Search

Exploring Transferable and Robust Adversarial Perturbation Generation from the Perspective of Network Hierarchy

1 code implementation16 Aug 2021 Ruikui Wang, Yuanfang Guo, Ruijie Yang, Yunhong Wang

In this paper, we explore effective mechanisms to boost both of them from the perspective of network hierarchy, where a typical network can be hierarchically divided into output stage, intermediate stage and input stage.

Video Person Re-identification using Attribute-enhanced Features

no code implementations16 Aug 2021 Tianrui Chai, ZhiYuan Chen, Annan Li, Jiaxin Chen, Xinyu Mei, Yunhong Wang

Video-based person re-identification (Re-ID) which aims to associate people across non-overlapping cameras using surveillance video is a challenging task.

Attribute Video-Based Person Re-Identification

Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning

1 code implementation15 Aug 2021 Jiahao Wang, Yunhong Wang, Sheng Liu, Annan Li

Fine-grained action recognition is attracting increasing attention due to the emerging demand of specific action understanding in real-world applications, whereas the data of rare fine-grained categories is very limited.

Action Understanding Fine-grained Action Recognition +1

Silhouette based View embeddings for Gait Recognition under Multiple Views

1 code implementation12 Aug 2021 Tianrui Chai, Xinyu Mei, Annan Li, Yunhong Wang

Gait recognition under multiple views is an important computer vision and pattern recognition task.

Gait Recognition

Cross-View Gait Recognition With Deep Universal Linear Embeddings

no code implementations CVPR 2021 Shaoxiong Zhang, Yunhong Wang, Annan Li

Furthermore, a novel framework based on convolutional variational autoencoder and deep Koopman embedding is proposed to approximate the Koopman operators, which is used as dynamical features from the linearized embedding space for cross-view gait recognition.

Gait Recognition

Pixel Sampling for Style Preserving Face Pose Editing

no code implementations14 Jun 2021 Xiangnan Yin, Di Huang, Hongyu Yang, Zehua Fu, Yunhong Wang, Liming Chen

The existing auto-encoder based face pose editing methods primarily focus on modeling the identity preserving ability during pose synthesis, but are less able to preserve the image style properly, which refers to the color, brightness, saturation, etc.

Facial Inpainting

Visual Grounding with Transformers

1 code implementation10 May 2021 Ye Du, Zehua Fu, Qingjie Liu, Yunhong Wang

In this paper, we propose a transformer based approach for visual grounding.

A Perceptual Distortion Reduction Framework: Towards Generating Adversarial Examples with High Perceptual Quality and Attack Success Rate

no code implementations1 May 2021 Ruijie Yang, Yunhong Wang, Ruikui Wang, Yuanfang Guo

This portion of distortions, which is induced by unnecessary modifications and lack of proper perceptual distortion constraint, is the target of the proposed framework.

Adversarial Attack

STMTrack: Template-free Visual Tracking with Space-time Memory Networks

1 code implementation CVPR 2021 Zhihong Fu, Qingjie Liu, Zehua Fu, Yunhong Wang

Boosting performance of the offline trained siamese trackers is getting harder nowadays since the fixed information of the template cropped from the first frame has been almost thoroughly mined, but they are poorly capable of resisting target appearance changes.

Visual Object Tracking Visual Tracking

MRDet: A Multi-Head Network for Accurate Oriented Object Detection in Aerial Images

no code implementations24 Dec 2020 Ran Qin, Qingjie Liu, Guangshuai Gao, Di Huang, Yunhong Wang

Objects in aerial images usually have arbitrary orientations and are densely located over the ground, making them extremely challenge to be detected.

object-detection Object Detection In Aerial Images +2

Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks

no code implementations20 Dec 2020 Hao Zeng, Qingjie Liu, Mingming Zhang, Xiaoqing Han, Yunhong Wang

To further lift the classification performance, in this work we propose a graph convolution network (GCN) based framework for HSI classification that uses two clustering operations to better exploit multi-hop node correlations and also effectively reduce graph size.

Classification Clustering +4

PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection

no code implementations18 Dec 2020 Yanan Zhang, Di Huang, Yunhong Wang

LiDAR-based 3D object detection is an important task for autonomous driving and current approaches suffer from sparse and partial point clouds of distant and occluded objects.

3D Object Detection Autonomous Driving +2

PGMAN: An Unsupervised Generative Multi-adversarial Network for Pan-sharpening

1 code implementation16 Dec 2020 Huanyu Zhou, Qingjie Liu, Yunhong Wang

However, since there are no intended HR MS images as references for learning, almost all of the existing methods down-sample the MS and PAN images and regard the original MS images as targets to form a supervised setting for training.

PSGCNet: A Pyramidal Scale and Global Context Guided Network for Dense Object Counting in Remote Sensing Images

1 code implementation7 Dec 2020 Guangshuai Gao, Qingjie Liu, Zhenghui Hu, Lu Li, Qi Wen, Yunhong Wang

Object counting, which aims to count the accurate number of object instances in images, has been attracting more and more attention.

Crowd Counting Object +1

ARM: A Confidence-Based Adversarial Reweighting Module for Coarse Semantic Segmentation

no code implementations11 Sep 2020 Jingchao Liu, Ye Du, Zehua Fu, Qingjie Liu, Yunhong Wang

Experiments on standard datasets shows our ARM can bring consistent improvements for both coarse annotations and fine annotations.

Semantic Segmentation

Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark Method

1 code implementation28 Aug 2020 Guangshuai Gao, Qingjie Liu, Yunhong Wang

Object counting, whose aim is to estimate the number of objects from a given image, is an important and challenging computation task.

Crowd Counting Object +1

Multi-Scale Positive Sample Refinement for Few-Shot Object Detection

4 code implementations ECCV 2020 Jiaxi Wu, Songtao Liu, Di Huang, Yunhong Wang

Few-shot object detection (FSOD) helps detectors adapt to unseen classes with few training instances, and is useful when manual annotation is time-consuming or data acquisition is limited.

Few-Shot Object Detection Object +1

Attribute-aware Identity-hard Triplet Loss for Video-based Person Re-identification

2 code implementations13 Jun 2020 Zhiyuan Chen, Annan Li, Shilu Jiang, Yunhong Wang

Video-based person re-identification (Re-ID) is an important computer vision task.

Attribute Metric Learning +1

Cycle-CNN for Colorization towards Real Monochrome-Color Camera Systems

1 code implementation AAAI Technical Track: Vision 2020 Xuan Dong, Weixin Li, Xiaojie Wang, Yunhong Wang

We present a new CNN model, named cycle CNN, which can directly use the real data from monochrome-color camera systems for training.

Colorization

CNN-based Density Estimation and Crowd Counting: A Survey

3 code implementations28 Mar 2020 Guangshuai Gao, Junyu. Gao, Qingjie Liu, Qi. Wang, Yunhong Wang

Through our analysis, we expect to make reasonable inference and prediction for the future development of crowd counting, and meanwhile, it can also provide feasible solutions for the problem of object counting in other fields.

Crowd Counting Density Estimation +1

Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation

no code implementations CVPR 2020 Yangtao Zheng, Di Huang, Songtao Liu, Yunhong Wang

Thanks to this coarse-to-fine feature adaptation, domain knowledge in foreground regions can be effectively transferred.

object-detection Object Detection

From W-Net to CDGAN: Bi-temporal Change Detection via Deep Learning Techniques

1 code implementation14 Mar 2020 Bin Hou, Qingjie Liu, Heng Wang, Yunhong Wang

Traditional change detection methods usually follow the image differencing, change feature extraction and classification framework, and their performance is limited by such simple image domain differencing and also the hand-crafted features.

Change Detection Generative Adversarial Network

Fake Generated Painting Detection via Frequency Analysis

no code implementations5 Mar 2020 Yong Bai, Yuanfang Guo, Jinjie Wei, Lin Lu, Rui Wang, Yunhong Wang

With the development of deep neural networks, digital fake paintings can be generated by various style transfer algorithms. To detect the fake generated paintings, we analyze the fake generated and real paintings in Fourier frequency domain and observe statistical differences and artifacts.

Style Transfer

Counting dense objects in remote sensing images

no code implementations14 Feb 2020 Guangshuai Gao, Qingjie Liu, Yunhong Wang

Significant efforts have been made to address this problem and achieve great progress, yet counting number of ground objects from remote sensing images is barely studied.

Object Counting

A Feasible Framework for Arbitrary-Shaped Scene Text Recognition

2 code implementations10 Dec 2019 Jinjin Zhang, Wei Wang, Di Huang, Qingjie Liu, Yunhong Wang

Deep learning based methods have achieved surprising progress in Scene Text Recognition (STR), one of classic problems in computer vision.

Instance Segmentation Language Modelling +4

Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism

no code implementations26 Nov 2019 Mingda Wu, Di Huang, Yuanfang Guo, Yunhong Wang

Recently, Human Attribute Recognition (HAR) has become a hot topic due to its scientific challenges and application potentials, where localizing attributes is a crucial stage but not well handled.

Attribute

Learning Spatial Fusion for Single-Shot Object Detection

1 code implementation21 Nov 2019 Songtao Liu, Di Huang, Yunhong Wang

Pyramidal feature representation is the common practice to address the challenge of scale variation in object detection.

Object object-detection +1

A Temporal Attentive Approach for Video-Based Pedestrian Attribute Recognition

no code implementations17 Jan 2019 Zhiyuan Chen, Annan Li, Yunhong Wang

In this paper, we first tackle the problem of pedestrian attribute recognition by video-based approach.

Attribute Pedestrian Attribute Recognition

Learning Continuous Face Age Progression: A Pyramid of GANs

no code implementations10 Jan 2019 Hongyu Yang, Di Huang, Yunhong Wang, Anil K. Jain

The two underlying requirements of face age progression, i. e. aging accuracy and identity permanence, are not well studied in the literature.

Face Recognition Generative Adversarial Network +1

Attentive Relational Networks for Mapping Images to Scene Graphs

no code implementations CVPR 2019 Mengshi Qi, Weijian Li, Zhengyuan Yang, Yunhong Wang, Jiebo Luo

Scene graph generation refers to the task of automatically mapping an image into a semantic structural graph, which requires correctly labeling each extracted object and their interaction relationships.

Graph Generation Object +4

Expressiveness in Deep Reinforcement Learning

no code implementations27 Sep 2018 Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang, Tie-Yan Liu

Based on our observations, we formally define expressiveness of the state extractor as the rank of the matrix composed by representations.

Atari Games reinforcement-learning +2

stagNet: An Attentive Semantic RNN for Group Activity Recognition

no code implementations ECCV 2018 Mengshi Qi, Jie Qin, Annan Li, Yunhong Wang, Jiebo Luo, Luc van Gool

Group activity recognition plays a fundamental role in a variety of applications, e. g. sports video analysis and intelligent surveillance.

Group Activity Recognition

PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening

1 code implementation9 May 2018 Qingjie Liu, Huanyu Zhou, Qizhi Xu, Xiangyu Liu, Yunhong Wang

This paper addresses the problem of remote sensing image pan-sharpening from the perspective of generative adversarial learning.

Generative Adversarial Network

Adversarial Binary Coding for Efficient Person Re-identification

no code implementations29 Mar 2018 Zheng Liu, Jie Qin, Annan Li, Yunhong Wang, Luc van Gool

Specifically, instead of learning explicit projections or adding fully-connected mapping layers, the proposed Adversarial Binary Coding (ABC) framework guides the extraction of binary codes implicitly and effectively.

Person Re-Identification

Learning Face Age Progression: A Pyramid Architecture of GANs

1 code implementation CVPR 2018 Hongyu Yang, Di Huang, Yunhong Wang, Anil K. Jain

The two underlying requirements of face age progression, i. e. aging accuracy and identity permanence, are not well studied in the literature.

Generative Adversarial Network

Feature Map Pooling for Cross-View Gait Recognition Based on Silhouette Sequence Images

no code implementations26 Nov 2017 Qiang Chen, Yunhong Wang, Zheng Liu, Qingjie Liu, Di Huang

In this paper, we develop a novel convolutional neural network based approach to extract and aggregate useful information from gait silhouette sequence images instead of simply representing the gait process by averaging silhouette images.

Gait Recognition

Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks

no code implementations21 Nov 2017 Xingyue Chen, Yunhong Wang, Qingjie Liu

Sentiment analysis is attracting more and more attentions and has become a very hot research topic due to its potential applications in personalized recommendation, opinion mining, etc.

Opinion Mining Sentiment Analysis

Receptive Field Block Net for Accurate and Fast Object Detection

7 code implementations ECCV 2018 Songtao Liu, Di Huang, Yunhong Wang

Current top-performing object detectors depend on deep CNN backbones, such as ResNet-101 and Inception, benefiting from their powerful feature representations but suffering from high computational costs.

object-detection Real-Time Object Detection

Remote Sensing Image Fusion Based on Two-stream Fusion Network

1 code implementation7 Nov 2017 Xiangyu Liu, Qingjie Liu, Yunhong Wang

Unlike previous CNN based methods that consider pan-sharpening as a super resolution problem and perform pan-sharpening in pixel level, the proposed TFNet aims to fuse PAN and MS images in feature level and reconstruct the pan-sharpened image from the fused features.

Image Reconstruction Super-Resolution +1

Fast Person Re-Identification via Cross-Camera Semantic Binary Transformation

no code implementations CVPR 2017 Jiaxin Chen, Yunhong Wang, Jie Qin, Li Liu, Ling Shao

Numerous methods have been proposed for person re-identification, most of which however neglect the matching efficiency.

Person Re-Identification

Binary Coding for Partial Action Analysis With Limited Observation Ratios

no code implementations CVPR 2017 Jie Qin, Li Liu, Ling Shao, Bingbing Ni, Chen Chen, Fumin Shen, Yunhong Wang

Extensive experiments on four realistic action datasets in terms of three tasks (i. e., partial action retrieval, recognition and prediction) clearly show the superiority of PRBC over the state-of-the-art methods, along with significantly reduced memory load and computational costs during the online test.

Action Analysis Action Recognition +3

Face Aging Effect Simulation using Hidden Factor Analysis Joint Sparse Representation

no code implementations4 Nov 2015 Hongyu Yang, Di Huang, Yunhong Wang, Heng Wang, Yuanyan Tang

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images.

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