Search Results for author: Feiyue Huang

Found 94 papers, 44 papers with code

SSCGAN: Facial Attribute Editing via Style Skip Connections

no code implementations ECCV 2020 Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji

Each connection extracts the style feature of the latent feature maps in the encoder and then performs a residual learning based mapping function in the global information space guided by the target attributes.

Enabling Deep Residual Networks for Weakly Supervised Object Detection

no code implementations ECCV 2020 Yunhang Shen, Rongrong Ji, Yan Wang, Zhiwei Chen, Feng Zheng, Feiyue Huang, Yunsheng Wu

Weakly supervised object detection (WSOD) has attracted extensive research attention due to its great flexibility of exploiting large-scale image-level annotation for detector training.

Weakly Supervised Object Detection

Towards Language-guided Visual Recognition via Dynamic Convolutions

no code implementations17 Oct 2021 Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Xinghao Ding, Yongjian Wu, Feiyue Huang, Yue Gao, Rongrong Ji

Based on the LaConv module, we further build the first fully language-driven convolution network, termed as LaConvNet, which can unify the visual recognition and multi-modal reasoning in one forward structure.

Question Answering Referring Expression Comprehension +1

Transformer-based Dual Relation Graph for Multi-label Image Recognition

no code implementations ICCV 2021 Jiawei Zhao, Ke Yan, Yifan Zhao, Xiaowei Guo, Feiyue Huang, Jia Li

Different from these researches, in this paper, we propose a novel Transformer-based Dual Relation learning framework, constructing complementary relationships by exploring two aspects of correlation, i. e., structural relation graph and semantic relation graph.

Fine-grained Data Distribution Alignment for Post-Training Quantization

1 code implementation9 Sep 2021 Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Feiyue Huang, Rongrong Ji

To alleviate this limitation, in this paper, we leverage the synthetic data introduced by zero-shot quantization with calibration dataset and we propose a fine-grained data distribution alignment (FDDA) method to boost the performance of post-training quantization.


Spatiotemporal Inconsistency Learning for DeepFake Video Detection

no code implementations4 Sep 2021 Zhihao Gu, Yang Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Lizhuang Ma

To address this issue, we term this task as a Spatial-Temporal Inconsistency Learning (STIL) process and instantiate it into a novel STIL block, which consists of a Spatial Inconsistency Module (SIM), a Temporal Inconsistency Module (TIM), and an Information Supplement Module (ISM).

Face Swapping

Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing

no code implementations5 Aug 2021 Shubao Liu, Ke-Yue Zhang, Taiping Yao, Mingwei Bi, Shouhong Ding, Jilin Li, Feiyue Huang, Lizhuang Ma

However, little attention has been paid to the feature extraction process for the FAS task, especially the influence of normalization, which also has a great impact on the generalization of the learned representation.

Domain Generalization Face Anti-Spoofing +1

Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework

1 code implementation27 Jul 2021 Qingyu Song, Changan Wang, Zhengkai Jiang, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yang Wu

In this paper, we propose a purely point-based framework for joint crowd counting and individual localization.

Crowd Counting

Discriminator-Free Generative Adversarial Attack

1 code implementation20 Jul 2021 ShaoHao Lu, Yuqiao Xian, Ke Yan, Yi Hu, Xing Sun, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng

The Deep Neural Networks are vulnerable toadversarial exam-ples(Figure 1), making the DNNs-based systems collapsed byadding the inconspicuous perturbations to the images.

Adversarial Attack

Learning To Restore Hazy Video: A New Real-World Dataset and a New Method

no code implementations CVPR 2021 Xinyi Zhang, Hang Dong, Jinshan Pan, Chao Zhu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Fei Wang

On the other hand, the video dehazing algorithms, which can acquire more satisfying dehazing results by exploiting the temporal redundancy from neighborhood hazy frames, receive less attention due to the absence of the video dehazing datasets.

Image Dehazing

RSTNet: Captioning With Adaptive Attention on Visual and Non-Visual Words

1 code implementation CVPR 2021 Xuying Zhang, Xiaoshuai Sun, Yunpeng Luo, Jiayi Ji, Yiyi Zhou, Yongjian Wu, Feiyue Huang, Rongrong Ji

Then, we build a BERTbased language model to extract language context and propose Adaptive-Attention (AA) module on top of a transformer decoder to adaptively measure the contribution of visual and language cues before making decisions for word prediction.

Image Captioning Language Modelling +2

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

no code implementations CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

no code implementations18 Jun 2021 YuHan Wang, Xu Chen, Junwei Zhu, Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Yongjian Wu, Feiyue Huang, Rongrong Ji

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results.

3D Face Reconstruction Face Recognition +1

Consistent Instance False Positive Improves Fairness in Face Recognition

1 code implementation CVPR 2021 Xingkun Xu, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jilin Li, Feiyue Huang, Yong Li, Zhen Cui

Then, an additional penalty term, which is in proportion to the ratio of instance FPR overall FPR, is introduced into the denominator of the softmax-based loss.

Face Recognition Fairness

Adaptive Feature Alignment for Adversarial Training

no code implementations31 May 2021 Tao Wang, Ruixin Zhang, Xingyu Chen, Kai Zhao, Xiaolin Huang, Yuge Huang, Shaoxin Li, Jilin Li, Feiyue Huang

Based on this observation, we propose the adaptive feature alignment (AFA) to generate features of arbitrary attacking strengths.

Adversarial Defense

Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model

no code implementations31 May 2021 Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong liu

Inspired by biological evolution, we explain the rationality of Vision Transformer by analogy with the proven practical Evolutionary Algorithm (EA) and derive that both of them have consistent mathematical representation.

Image Retrieval

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

no code implementations6 May 2021 Zhihong Chen, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Feiyue Huang, Xinyu Jin

Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios.

Domain Generalization Face Anti-Spoofing +2

Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack

no code implementations3 May 2021 Yixu Wang, Jie Li, Hong Liu, Yan Wang, Yongjian Wu, Feiyue Huang, Rongrong Ji

We argue this is due to the lack of rich information in the probability prediction and the overfitting caused by hard labels.

Self-Knowledge Distillation

ISTR: End-to-End Instance Segmentation with Transformers

1 code implementation3 May 2021 Jie Hu, Liujuan Cao, Yao Lu, Shengchuan Zhang, Yan Wang, Ke Li, Feiyue Huang, Ling Shao, Rongrong Ji

However, such an upgrade is not applicable to instance segmentation, due to its significantly higher output dimensions compared to object detection.

 Ranked #1 on Object Detection on COCO test-dev (Hardware Burden metric)

Instance Segmentation Semantic Segmentation

Delving into Data: Effectively Substitute Training for Black-box Attack

no code implementations CVPR 2021 Wenxuan Wang, Bangjie Yin, Taiping Yao, Li Zhang, Yanwei Fu, Shouhong Ding, Jilin Li, Feiyue Huang, xiangyang xue

Previous substitute training approaches focus on stealing the knowledge of the target model based on real training data or synthetic data, without exploring what kind of data can further improve the transferability between the substitute and target models.

Adversarial Attack

Carrying out CNN Channel Pruning in a White Box

1 code implementation24 Apr 2021 Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji

Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner w. r. t.

Classification Image Classification

DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning

1 code implementation19 Apr 2021 Yuting Gao, Jia-Xin Zhuang, Ke Li, Hao Cheng, Xiaowei Guo, Feiyue Huang, Rongrong Ji, Xing Sun

Specifically, we find the final embedding obtained by the mainstream SSL methods contains the most fruitful information, and propose to distill the final embedding to maximally transmit a teacher's knowledge to a lightweight model by constraining the last embedding of the student to be consistent with that of the teacher.

Contrastive Learning Representation Learning +1

Distilling a Powerful Student Model via Online Knowledge Distillation

1 code implementation26 Mar 2021 Shaojie Li, Mingbao Lin, Yan Wang, Feiyue Huang, Yongjian Wu, Yonghong Tian, Ling Shao, Rongrong Ji

To enable the student leader to absorb more diverse information, we design an enhancement strategy to increase the diversity among students.

Knowledge Distillation

On Evolving Attention Towards Domain Adaptation

no code implementations25 Mar 2021 Kekai Sheng, Ke Li, Xiawu Zheng, Jian Liang, WeiMing Dong, Feiyue Huang, Rongrong Ji, Xing Sun

However, considering that the configuration of attention, i. e., the type and the position of attention module, affects the performance significantly, it is more generalized to optimize the attention configuration automatically to be specialized for arbitrary UDA scenario.

Unsupervised Domain Adaptation

Learning Dynamic Alignment via Meta-filter for Few-shot Learning

1 code implementation CVPR 2021 Chengming Xu, Chen Liu, Li Zhang, Chengjie Wang, Jilin Li, Feiyue Huang, xiangyang xue, Yanwei Fu

Our insight is that these methods would lead to poor adaptation with redundant matching, and leveraging channel-wise adjustment is the key to well adapting the learned knowledge to new classes.

Few-Shot Learning

Learning Comprehensive Motion Representation for Action Recognition

no code implementations23 Mar 2021 Mingyu Wu, Boyuan Jiang, Donghao Luo, Junchi Yan, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Xiaokang Yang

For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame.

Action Recognition

Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Xingjia Pan, Yingguo Gao, Zhiwen Lin, Fan Tang, WeiMing Dong, Haolei Yuan, Feiyue Huang, Changsheng Xu

Weakly supervised object localization(WSOL) remains an open problem given the deficiency of finding object extent information using a classification network.

Classification General Classification +1

Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query

1 code implementation ICCV 2021 Guanyu Cai, Jun Zhang, Xinyang Jiang, Yifei Gong, Lianghua He, Fufu Yu, Pai Peng, Xiaowei Guo, Feiyue Huang, Xing Sun

However, the performance of existing methods suffers in real life since the user is likely to provide an incomplete description of an image, which often leads to results filled with false positives that fit the incomplete description.

Cross-Modal Retrieval Image Retrieval

Image-to-image Translation via Hierarchical Style Disentanglement

1 code implementation CVPR 2021 Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji

Recently, image-to-image translation has made significant progress in achieving both multi-label (\ie, translation conditioned on different labels) and multi-style (\ie, generation with diverse styles) tasks.

Multimodal Unsupervised Image-To-Image Translation Translation

Network Pruning using Adaptive Exemplar Filters

1 code implementation20 Jan 2021 Mingbao Lin, Rongrong Ji, Shaojie Li, Yan Wang, Yongjian Wu, Feiyue Huang, Qixiang Ye

Inspired by the face recognition community, we use a message passing algorithm Affinity Propagation on the weight matrices to obtain an adaptive number of exemplars, which then act as the preserved filters.

Face Recognition Network Pruning

Dual-Level Collaborative Transformer for Image Captioning

1 code implementation16 Jan 2021 Yunpeng Luo, Jiayi Ji, Xiaoshuai Sun, Liujuan Cao, Yongjian Wu, Feiyue Huang, Chia-Wen Lin, Rongrong Ji

Descriptive region features extracted by object detection networks have played an important role in the recent advancements of image captioning.

Image Captioning Object Detection

Aha! Adaptive History-Driven Attack for Decision-Based Black-Box Models

no code implementations ICCV 2021 Jie Li, Rongrong Ji, Peixian Chen, Baochang Zhang, Xiaopeng Hong, Ruixin Zhang, Shaoxin Li, Jilin Li, Feiyue Huang, Yongjian Wu

A common practice is to start from a large perturbation and then iteratively reduce it with a deterministic direction and a random one while keeping it adversarial.

Dimensionality Reduction

Frequency Consistent Adaptation for Real World Super Resolution

no code implementations18 Dec 2020 Xiaozhong Ji, Guangpin Tao, Yun Cao, Ying Tai, Tong Lu, Chengjie Wang, Jilin Li, Feiyue Huang

From this point of view, we design a novel Frequency Consistent Adaptation (FCA) that ensures the frequency domain consistency when applying existing SR methods to the real scene.


Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation

no code implementations4 Dec 2020 Zhiyong Huang, Kekai Sheng, WeiMing Dong, Xing Mei, Chongyang Ma, Feiyue Huang, Dengwen Zhou, Changsheng Xu

For intra-domain propagation, we propose an effective self-training strategy to mitigate the noises in pseudo-labeled target domain data and improve the feature discriminability in the target domain.

Domain Adaptation Image Classification

UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection

1 code implementation NeurIPS 2020 Yunhang Shen, Rongrong Ji, Zhiwei Chen, Yongjian Wu, Feiyue Huang

In this paper, we propose a unified WSOD framework, termed UWSOD, to develop a high-capacity general detection model with only image-level labels, which is self-contained and does not require external modules or additional supervision.

Object Proposal Generation Weakly Supervised Object Detection

Fast Class-wise Updating for Online Hashing

no code implementations1 Dec 2020 Mingbao Lin, Rongrong Ji, Xiaoshuai Sun, Baochang Zhang, Feiyue Huang, Yonghong Tian, DaCheng Tao

To achieve fast online adaptivity, a class-wise updating method is developed to decompose the binary code learning and alternatively renew the hash functions in a class-wise fashion, which well addresses the burden on large amounts of training batches.

Adversarial Refinement Network for Human Motion Prediction

no code implementations23 Nov 2020 Xianjin Chao, Yanrui Bin, Wenqing Chu, Xuan Cao, Yanhao Ge, Chengjie Wang, Jilin Li, Feiyue Huang, Howard Leung

Specifically, we take both the historical motion sequences and coarse prediction as input of our cascaded refinement network to predict refined human motion and strengthen the refinement network with adversarial error augmentation.

Human motion prediction motion prediction

Rotated Binary Neural Network

2 code implementations NeurIPS 2020 Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin

In this paper, for the first time, we explore the influence of angular bias on the quantization error and then introduce a Rotated Binary Neural Network (RBNN), which considers the angle alignment between the full-precision weight vector and its binarized version.

Binarization Quantization

Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning

2 code implementations CVPR 2021 Jinpeng Wang, Yuting Gao, Ke Li, Yiqi Lin, Andy J. Ma, Hao Cheng, Pai Peng, Feiyue Huang, Rongrong Ji, Xing Sun

Then we force the model to pull the feature of the distracting video and the feature of the original video closer, so that the model is explicitly restricted to resist the background influence, focusing more on the motion changes.

Representation Learning Self-Supervised Learning

Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

1 code implementation ECCV 2020 Jinlong Peng, Changan Wang, Fangbin Wan, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yanwei Fu

Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or have two of the three subtasks integrated to form a partially end-to-end solution.

Multiple Object Tracking Object Detection

NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination

1 code implementation27 Jul 2020 Penghao Zhou, Chong Zhou, Pai Peng, Junlong Du, Xing Sun, Xiaowei Guo, Feiyue Huang

Greedy-NMS inherently raises a dilemma, where a lower NMS threshold will potentially lead to a lower recall rate and a higher threshold introduces more false positives.

Object Detection Pedestrian Detection

Temporal Distinct Representation Learning for Action Recognition

no code implementations ECCV 2020 Junwu Weng, Donghao Luo, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Xudong Jiang, Junsong Yuan

Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos.

Action Recognition Representation Learning

Collaborative Learning for Faster StyleGAN Embedding

no code implementations3 Jul 2020 Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, Xiaokang Yang

The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator.

ACFD: Asymmetric Cartoon Face Detector

no code implementations2 Jul 2020 Bin Zhang, Jian Li, Yabiao Wang, Zhipeng Cui, Yili Xia, Chengjie Wang, Jilin Li, Feiyue Huang

Cartoon face detection is a more challenging task than human face detection due to many difficult scenarios is involved.

Face Detection

Arbitrary Style Transfer via Multi-Adaptation Network

1 code implementation27 May 2020 Yingying Deng, Fan Tang, Wei-Ming Dong, Wen Sun, Feiyue Huang, Changsheng Xu

Arbitrary style transfer is a significant topic with research value and application prospect.

Style Transfer

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

1 code implementation CVPR 2020 Yuge Huang, YuHan Wang, Ying Tai, Xiaoming Liu, Pengcheng Shen, Shaoxin Li, Jilin Li, Feiyue Huang

As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability.

Curriculum Learning Face Recognition

Towards Palmprint Verification On Smartphones

no code implementations30 Mar 2020 Yingyi Zhang, Lin Zhang, Ruixin Zhang, Shaoxin Li, Jilin Li, Feiyue Huang

First, to facilitate the study of palmprint verification on smartphones, we established an annotated palmprint dataset named MPD, which was collected by multi-brand smartphones in two separate sessions with various backgrounds and illumination conditions.

Architecture Disentanglement for Deep Neural Networks

1 code implementation ICCV 2021 Jie Hu, Liujuan Cao, Qixiang Ye, Tong Tong, Shengchuan Zhang, Ke Li, Feiyue Huang, Rongrong Ji, Ling Shao

Based on the experimental results, we present three new findings that provide fresh insights into the inner logic of DNNs.


ASFD: Automatic and Scalable Face Detector

no code implementations25 Mar 2020 Bin Zhang, Jian Li, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yili Xia, Wenjiang Pei, Rongrong Ji

In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design.

Neural Architecture Search

Improving Face Recognition from Hard Samples via Distribution Distillation Loss

2 code implementations ECCV 2020 Yuge Huang, Pengcheng Shen, Ying Tai, Shaoxin Li, Xiaoming Liu, Jilin Li, Feiyue Huang, Rongrong Ji

To improve the performance on those hard samples for general tasks, we propose a novel Distribution Distillation Loss to narrow the performance gap between easy and hard samples, which is a simple, effective and generic for various types of facial variations.

Face Recognition

Learning Semantic Neural Tree for Human Parsing

no code implementations ECCV 2020 Ruyi Ji, Dawei Du, Libo Zhang, Longyin Wen, Yanjun Wu, Chen Zhao, Feiyue Huang, Siwei Lyu

In this paper, we design a novel semantic neural tree for human parsing, which uses a tree architecture to encode physiological structure of human body, and designs a coarse to fine process in a cascade manner to generate accurate results.

Human Parsing Semantic Segmentation

Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification

1 code implementation3 Dec 2019 Zhihui Zhu, Xinyang Jiang, Feng Zheng, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng, Xing Sun

Instead of one subspace for each viewpoint, our method projects the feature from different viewpoints into a unified hypersphere and effectively models the feature distribution on both the identity-level and the viewpoint-level.

Ranked #5 on Person Re-Identification on DukeMTMC-reID (using extra training data)

Person Re-Identification

Variational Structured Semantic Inference for Diverse Image Captioning

no code implementations NeurIPS 2019 Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang

To model these two inherent diversities in image captioning, we propose a Variational Structured Semantic Inferring model (termed VSSI-cap) executed in a novel structured encoder-inferer-decoder schema.

Image Captioning

Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect

2 code implementations28 Nov 2019 Xinyang Jiang, Yifei Gong, Xiaowei Guo, Qize Yang, Feiyue Huang, Wei-Shi Zheng, Feng Zheng, Xing Sun

Recently, the research interest of person re-identification (ReID) has gradually turned to video-based methods, which acquire a person representation by aggregating frame features of an entire video.

Video-Based Person Re-Identification

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

no code implementations26 Nov 2019 Kekai Sheng, Wei-Ming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma

In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.

TEINet: Towards an Efficient Architecture for Video Recognition

no code implementations21 Nov 2019 Zhao-Yang Liu, Donghao Luo, Yabiao Wang, Li-Min Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Tong Lu

To relieve this problem, we propose an efficient temporal module, termed as Temporal Enhancement-and-Interaction (TEI Module), which could be plugged into the existing 2D CNNs (denoted by TEINet).

Action Recognition Video Recognition

Fast Learning of Temporal Action Proposal via Dense Boundary Generator

3 code implementations11 Nov 2019 Chuming Lin, Jian Li, Yabiao Wang, Ying Tai, Donghao Luo, Zhipeng Cui, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji

In this paper, we propose an efficient and unified framework to generate temporal action proposals named Dense Boundary Generator (DBG), which draws inspiration from boundary-sensitive methods and implements boundary classification and action completeness regression for densely distributed proposals.

General Classification Optical Flow Estimation

Semantic-aware Image Deblurring

no code implementations9 Oct 2019 Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xiaoshuai Sun, Chia-Wen Lin, Jiayi Ji, Baochang Zhang, Feiyue Huang, Liujuan Cao

Specially, we propose a novel Structured-Spatial Semantic Embedding model for image deblurring (termed S3E-Deblur), which introduces a novel Structured-Spatial Semantic tree model (S3-tree) to bridge two basic tasks in computer vision: image deblurring (ImD) and image captioning (ImC).

Deblurring Image Captioning

Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization

2 code implementations CVPR 2020 Ruyi Ji, Longyin Wen, Libo Zhang, Dawei Du, Yanjun Wu, Chen Zhao, Xianglong Liu, Feiyue Huang

Specifically, we incorporate convolutional operations along edges of the tree structure, and use the routing functions in each node to determine the root-to-leaf computational paths within the tree.

Fine-Grained Image Classification Fine-Grained Visual Categorization

Semi-Supervised Adversarial Monocular Depth Estimation

no code implementations6 Aug 2019 Rongrong Ji, Ke Li, Yan Wang, Xiaoshuai Sun, Feng Guo, Xiaowei Guo, Yongjian Wu, Feiyue Huang, Jiebo Luo

In this paper, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available.

Monocular Depth Estimation

Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently

no code implementations11 Jun 2019 Dan Liu, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu, Feiyue Huang, Siwei Lyu

Existing hand detection methods usually follow the pipeline of multiple stages with high computation cost, i. e., feature extraction, region proposal, bounding box regression, and additional layers for rotated region detection.

Hand Detection Region Proposal

Interpretable Neural Network Decoupling

no code implementations ECCV 2020 Yuchao Li, Rongrong Ji, Shaohui Lin, Baochang Zhang, Chenqian Yan, Yongjian Wu, Feiyue Huang, Ling Shao

More specifically, we introduce a novel architecture controlling module in each layer to encode the network architecture by a vector.

Supervised Online Hashing via Similarity Distribution Learning

no code implementations31 May 2019 Mingbao Lin, Rongrong Ji, Shen Chen, Feng Zheng, Xiaoshuai Sun, Baochang Zhang, Liujuan Cao, Guodong Guo, Feiyue Huang

In this paper, we propose to model the similarity distributions between the input data and the hashing codes, upon which a novel supervised online hashing method, dubbed as Similarity Distribution based Online Hashing (SDOH), is proposed, to keep the intrinsic semantic relationship in the produced Hamming space.

LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning

1 code implementation15 May 2019 Huaiyu Li, Wei-Ming Dong, Xing Mei, Chongyang Ma, Feiyue Huang, Bao-Gang Hu

The TargetNet module is a neural network for solving a specific task and the MetaNet module aims at learning to generate functional weights for TargetNet by observing training samples.

Few-Shot Learning

Anti-Confusing: Region-Aware Network for Human Pose Estimation

no code implementations3 May 2019 Xuan Cao, Yanhao Ge, Ying Tai, Wei zhang, Jian Li, Chengjie Wang, Jilin Li, Feiyue Huang

In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric appearance, for human pose estimation.

Data Augmentation Pose Estimation

Towards Optimal Structured CNN Pruning via Generative Adversarial Learning

no code implementations CVPR 2019 Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, David Doermann

In this paper, we propose an effective structured pruning approach that jointly prunes filters as well as other structures in an end-to-end manner.

Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection

no code implementations27 Feb 2019 Yao Liu, Ying Tai, Jilin Li, Shouhong Ding, Chengjie Wang, Feiyue Huang, Dongyang Li, Wenshuai Qi, Rongrong Ji

In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-world systems serving for millions of users.

Face Anti-Spoofing General Classification

Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression

1 code implementation CVPR 2019 Yuchao Li, Shaohui Lin, Baochang Zhang, Jianzhuang Liu, David Doermann, Yongjian Wu, Feiyue Huang, Rongrong Ji

The relationship between the input feature maps and 2D kernels is revealed in a theoretical framework, based on which a kernel sparsity and entropy (KSE) indicator is proposed to quantitate the feature map importance in a feature-agnostic manner to guide model compression.

Model Compression

Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

1 code implementation1 Nov 2018 Ying Tai, Yicong Liang, Xiaoming Liu, Lei Duan, Jilin Li, Chengjie Wang, Feiyue Huang, Yu Chen

In recent years, heatmap regression based models have shown their effectiveness in face alignment and pose estimation.

Face Alignment Pose Estimation +1

Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training

1 code implementation CVPR 2019 Feng Zheng, Cheng Deng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang, Rongrong Ji

Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other.

Person Re-Identification

DSFD: Dual Shot Face Detector

3 code implementations CVPR 2019 Jian Li, Yabiao Wang, Changan Wang, Ying Tai, Jianjun Qian, Jian Yang, Chengjie Wang, Jilin Li, Feiyue Huang

In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively.

Data Augmentation Face Detection

Attention-based Multi-Patch Aggregation for Image Aesthetic Assessment

1 code implementation ACM Multimedia Conference 2018 Kekai Sheng, Wei-Ming Dong, Chongyang Ma, Xing Mei, Feiyue Huang, Bao-Gang Hu

Aggregation structures with explicit information, such as image attributes and scene semantics, are effective and popular for intelligent systems for assessing aesthetics of visual data.

Aesthetics Quality Assessment

Adversarial Attribute-Image Person Re-identification

no code implementations5 Dec 2017 Zhou Yin, Wei-Shi Zheng, An-Cong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue Huang, Jian-Huang Lai

While attributes have been widely used for person re-identification (Re-ID) which aims at matching the same person images across disjoint camera views, they are used either as extra features or for performing multi-task learning to assist the image-image matching task.

Multi-Task Learning Person Re-Identification

Cross-Modality Binary Code Learning via Fusion Similarity Hashing

no code implementations CVPR 2017 Hong Liu, Rongrong Ji, Yongjian Wu, Feiyue Huang, Baochang Zhang

In this paper, we propose a hashing scheme, termed Fusion Similarity Hashing (FSH), which explicitly embeds the graph-based fusion similarity across modalities into a common Hamming space.

Fast and Accurate Neural Word Segmentation for Chinese

1 code implementation ACL 2017 Deng Cai, Hai Zhao, Zhisong Zhang, Yuan Xin, Yongjian Wu, Feiyue Huang

Neural models with minimal feature engineering have achieved competitive performance against traditional methods for the task of Chinese word segmentation.

Chinese Word Segmentation Feature Engineering

Ordinal Constrained Binary Code Learning for Nearest Neighbor Search

no code implementations19 Nov 2016 Hong Liu, Rongrong Ji, Yongjian Wu, Feiyue Huang

By given a large-scale training data set, it is very expensive to embed such ranking tuples in binary code learning.

Small Data Image Classification

Automatic Script Identification in the Wild

no code implementations12 May 2015 Baoguang Shi, Cong Yao, Chengquan Zhang, Xiaowei Guo, Feiyue Huang, Xiang Bai

With the rapid increase of transnational communication and cooperation, people frequently encounter multilingual scenarios in various situations.

General Classification Image Classification

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