Search Results for author: Hao Li

Found 196 papers, 67 papers with code

Unsupervised Representation Learning for 3D MRI Super Resolution with Degradation Adaptation

no code implementations13 May 2022 Jianan Liu, Hao Li, Tao Huang, Euijoon Ahn, Adeel Razi, Wei Xiang

Therefore, most of the previous studies proposed SR reconstruction by employing authentic HR images and synthetic LR images downsampled from the HR images, yet the difference in degradation representations between synthetic and authentic LR images suppresses the performance of SR reconstruction from authentic LR images.

Image Registration Representation Learning +1

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Joint learning of object graph and relation graph for visual question answering

no code implementations9 May 2022 Hao Li, Xu Li, Belhal Karimi, Jie Chen, Mingming Sun

Modeling visual question answering(VQA) through scene graphs can significantly improve the reasoning accuracy and interpretability.

Question Answering Visual Question Answering +1

Multi-view Point Cloud Registration based on Evolutionary Multitasking with Bi-Channel Knowledge Sharing Mechanism

no code implementations6 May 2022 Yue Wu, Yibo Liu, Maoguo Gong, Hao Li, Zedong Tang, Qiguang Miao, Wenping Ma

The intra-task knowledge sharing introduces aiding tasks that are much simpler to solve, and useful information is shared within tasks, accelerating the search process.

3D Reconstruction Point Cloud Registration

Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion

no code implementations18 Apr 2022 Evonne Ng, Hanbyul Joo, Liwen Hu, Hao Li, Trevor Darrell, Angjoo Kanazawa, Shiry Ginosar

We present a framework for modeling interactional communication in dyadic conversations: given multimodal inputs of a speaker, we autoregressively output multiple possibilities of corresponding listener motion.

Task Adaptive Parameter Sharing for Multi-Task Learning

no code implementations30 Mar 2022 Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless Fowlkes, Rahul Bhotika, Stefano Soatto

TAPS solves a joint optimization problem which determines which layers to share with the base model and the value of the task-specific weights.

Multi-Task Learning

EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

1 code implementation24 Mar 2022 Hansheng Chen, Pichao Wang, Fan Wang, Wei Tian, Lu Xiong, Hao Li

The 2D-3D coordinates and corresponding weights are treated as intermediate variables learned by minimizing the KL divergence between the predicted and target pose distribution.

3D Object Detection 6D Pose Estimation using RGB

PMAL: Open Set Recognition via Robust Prototype Mining

no code implementations16 Mar 2022 Jing Lu, Yunxu Xu, Hao Li, Zhanzhan Cheng, Yi Niu

Accordingly, the embedding space can be better optimized to discriminate therein the predefined classes and between known and unknowns.

Open Set Learning

On Representation Learning with Feedback

1 code implementation15 Feb 2022 Hao Li

This note complements the author's recent paper "Robust representation learning with feedback for single image deraining" by providing heuristically theoretical explanations on the mechanism of representation learning with feedback, namely an essential merit of the works presented in this recent article.

Representation Learning Single Image Deraining

Image-to-Video Re-Identification via Mutual Discriminative Knowledge Transfer

no code implementations21 Jan 2022 Pichao Wang, Fan Wang, Hao Li

During the KD process, the TCL loss transfers the local structure, exploits the higher order information, and mitigates the misalignment of the heterogeneous output of teacher and student networks.

Knowledge Distillation Transfer Learning

Studying Popular Open Source Machine Learning Libraries and Their Cross-Ecosystem Bindings

1 code implementation18 Jan 2022 Hao Li, Cor-Paul Bezemer

Our study shows that the vast majority of the studied bindings cover only a small portion of the source library releases, and the delay for receiving support for a source library release is large.

Graph Neural Networks for Double-Strand DNA Breaks Prediction

no code implementations4 Jan 2022 Xu Wang, Huan Zhao, WeiWei Tu, Hao Li, Yu Sun, Xiaochen Bo

Double-strand DNA breaks (DSBs) are a form of DNA damage that can cause abnormal chromosomal rearrangements.

ELSA: Enhanced Local Self-Attention for Vision Transformer

1 code implementation23 Dec 2021 Jingkai Zhou, Pichao Wang, Fan Wang, Qiong Liu, Hao Li, Rong Jin

Self-attention is powerful in modeling long-range dependencies, but it is weak in local finer-level feature learning.

Image Classification Instance Segmentation +2

Watch Those Words: Video Falsification Detection Using Word-Conditioned Facial Motion

1 code implementation21 Dec 2021 Shruti Agarwal, Liwen Hu, Evonne Ng, Trevor Darrell, Hao Li, Anna Rohrbach

In today's era of digital misinformation, we are increasingly faced with new threats posed by video falsification techniques.


Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition

1 code implementation16 Dec 2021 Benjia Zhou, Pichao Wang, Jun Wan, Yanyan Liang, Fan Wang, Du Zhang, Zhen Lei, Hao Li, Rong Jin

Decoupling spatiotemporal representation refers to decomposing the spatial and temporal features into dimension-independent factors.

TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning

1 code implementation16 Dec 2021 Shiming Chen, Ziming Hong, Guo-Sen Xie, Jian Zhao, Hao Li, Xinge You, Shuicheng Yan, Ling Shao

Analogously, VAT uses the similar feature augmentation encoder to refine the visual features, which are further applied in visual$\rightarrow$attribute decoder to learn visual-based attribute features.

Zero-Shot Learning

On the Dilution of Precision for Time Difference of Arrival with Station Deployment

no code implementations10 Dec 2021 Fengyun Zhang, Hao Li, Yulong Ding, Shuang-Hua Yang, Li Yang

The paper aims to reveal the relationship between the performance of moving object tracking algorithms and the tracking anchors (station) deployment.

Object Tracking TAG

Design and Implementation of Real-Time Localization System (RTLS) based on UWB and TDoA Algorithm

no code implementations9 Dec 2021 Fengyun Zhang, Li Yang, Yuhuan Liu, Yulong Ding, Shuang-Hua Yang, Hao Li

The challenges of indoor localization include inadequate localization accuracy, unreasonable anchor deployment in complex scenarios, lack of stability, and high cost.

Indoor Localization

TransZero: Attribute-guided Transformer for Zero-Shot Learning

1 code implementation3 Dec 2021 Shiming Chen, Ziming Hong, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You

Although some attention-based models have attempted to learn such region features in a single image, the transferability and discriminative attribute localization of visual features are typically neglected.

Zero-Shot Learning

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

1 code implementation2 Dec 2021 Zhaoyuan Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin

Unsupervised semantic segmentation aims to obtain high-level semantic representation on low-level visual features without manual annotations.

Self-Supervised Learning Unsupervised Semantic Segmentation

Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks

no code implementations2 Dec 2021 Xizhou Zhu, Jinguo Zhu, Hao Li, Xiaoshi Wu, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, Jifeng Dai

The model is pre-trained on several uni-modal and multi-modal tasks, and evaluated on a variety of downstream tasks, including novel tasks that did not appear in the pre-training stage.

3D High-Quality Magnetic Resonance Image Restoration in Clinics Using Deep Learning

no code implementations28 Nov 2021 Hao Li, Jianan Liu

Specifically, most of the prior works focus solely on the network model but ignore the impact of various downsampling strategies on the acquisition time.

Image Restoration Super-Resolution

Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice

no code implementations24 Nov 2021 Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Antoni Chan, Rong Jin

Our result reveals that the final prediction precision may have a weak dependency on the pre-trained model especially in the case of large training iterations.

Image Classification Learning Theory

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

1 code implementation23 Nov 2021 Hao Luo, Pichao Wang, Yi Xu, Feng Ding, Yanxin Zhou, Fan Wang, Hao Li, Rong Jin

We first investigate self-supervised learning (SSL) methods with Vision Transformer (ViT) pretrained on unlabelled person images (the LUPerson dataset), and empirically find it significantly surpasses ImageNet supervised pre-training models on ReID tasks.

 Ranked #1 on Unsupervised Person Re-Identification on Market-1501 (using extra training data)

Self-Supervised Learning Unsupervised Domain Adaptation +1

Topologically Consistent Multi-View Face Inference Using Volumetric Sampling

no code implementations ICCV 2021 Tianye Li, Shichen Liu, Timo Bolkart, Jiayi Liu, Hao Li, Yajie Zhao

We propose ToFu, Topologically consistent Face from multi-view, a geometry inference framework that can produce topologically consistent meshes across facial identities and expressions using a volumetric representation instead of an explicit underlying 3DMM.

3D Reconstruction

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning

1 code implementation NeurIPS 2021 Shiming Chen, Guo-Sen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao

Specifically, HSVA aligns the semantic and visual domains by adopting a hierarchical two-step adaptation, i. e., structure adaptation and distribution adaptation.

Transfer Learning Zero-Shot Learning

NAS-Bench-Zero: A Large Scale Dataset for Understanding Zero-Shot Neural Architecture Search

no code implementations29 Sep 2021 Hanlin Chen, Ming Lin, Xiuyu Sun, Hao Li

Based on these new discoveries, we propose i) a novel hybrid zero-shot proxy which outperforms existing ones by a large margin and is transferable among popular search spaces; ii) a new index for better measuring the true performance of ZS-NAS proxies in constrained NAS.

Neural Architecture Search

Unsupervised Domain Adaptation By Optimal Transportation Of Clusters Between Domains

no code implementations29 Sep 2021 Yang Liu, Zhipeng Zhou, Lei Shang, Baigui Sun, Hao Li, Rong Jin

Unsupervised domain adaptation (UDA) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain.

Transfer Learning Unsupervised Domain Adaptation

Unsupervised Cross-Modality Domain Adaptation for Segmenting Vestibular Schwannoma and Cochlea with Data Augmentation and Model Ensemble

no code implementations24 Sep 2021 Hao Li, Dewei Hu, Qibang Zhu, Kathleen E. Larson, Huahong Zhang, Ipek Oguz

To overcome this problem, domain adaptation is an effective way to leverage information from source domain to obtain accurate segmentations without requiring manual labels in target domain.

Data Augmentation Domain Adaptation +2

Interpolation variable rate image compression

no code implementations20 Sep 2021 Zhenhong Sun, Zhiyu Tan, Xiuyu Sun, Fangyi Zhang, Yichen Qian, Dongyang Li, Hao Li

Compression standards have been used to reduce the cost of image storage and transmission for decades.

Image Compression MS-SSIM +1

DisUnknown: Distilling Unknown Factors for Disentanglement Learning

1 code implementation ICCV 2021 Sitao Xiang, Yuming Gu, Pengda Xiang, Menglei Chai, Hao Li, Yajie Zhao, Mingming He

In this paper, we adopt a general setting where all factors that are hard to label or identify are encapsulated as a single unknown factor.


CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

1 code implementation ICLR 2022 Tongkun Xu, Weihua Chen, Pichao Wang, Fan Wang, Hao Li, Rong Jin

Along with the pseudo labels, a weight-sharing triple-branch transformer framework is proposed to apply self-attention and cross-attention for source/target feature learning and source-target domain alignment, respectively.

Unsupervised Domain Adaptation

Scaled ReLU Matters for Training Vision Transformers

no code implementations8 Sep 2021 Pichao Wang, Xue Wang, Hao Luo, Jingkai Zhou, Zhipeng Zhou, Fan Wang, Hao Li, Rong Jin

In this paper, we further investigate this problem and extend the above conclusion: only early convolutions do not help for stable training, but the scaled ReLU operation in the \textit{convolutional stem} (\textit{conv-stem}) matters.

Dash: Semi-Supervised Learning with Dynamic Thresholding

no code implementations1 Sep 2021 Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin

In this work we develop a simple yet powerful framework, whose key idea is to select a subset of training examples from the unlabeled data when performing existing SSL methods so that only the unlabeled examples with pseudo labels related to the labeled data will be used to train models.

Semi-Supervised Image Classification

Digging into Uncertainty in Self-supervised Multi-view Stereo

1 code implementation ICCV 2021 Hongbin Xu, Zhipeng Zhou, Yali Wang, Wenxiong Kang, Baigui Sun, Hao Li, Yu Qiao

Specially, the limitations can be categorized into two types: ambiguious supervision in foreground and invalid supervision in background.

Image Reconstruction Self-Supervised Learning

Exploring the Quality of GAN Generated Images for Person Re-Identification

no code implementations23 Aug 2021 Yiqi Jiang, Weihua Chen, Xiuyu Sun, Xiaoyu Shi, Fan Wang, Hao Li

Recently, GAN based method has demonstrated strong effectiveness in generating augmentation data for person re-identification (ReID), on account of its ability to bridge the gap between domains and enrich the data variety in feature space.

Person Re-Identification Unsupervised Domain Adaptation

Fine-Grained AutoAugmentation for Multi-Label Classification

no code implementations12 Jul 2021 Ya Wang, Hesen Chen, Fangyi Zhang, Yaohua Wang, Xiuyu Sun, Ming Lin, Hao Li

Data augmentation is a commonly used approach to improving the generalization of deep learning models.

Classification Data Augmentation +3

A Cloud-Edge-Terminal Collaborative System for Temperature Measurement in COVID-19 Prevention

no code implementations11 Jul 2021 Zheyi Ma, Hao Li, Wen Fang, Qingwen Liu, Bin Zhou, Zhiyong Bu

Then, a mobile detection model based on a multi-task cascaded convolutional network (MTCNN) is proposed to realize face alignment and mask detection on the RGB images.

Face Alignment

LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation

no code implementations9 Jul 2021 Dewei Hu, Can Cui, Hao Li, Kathleen E. Larson, Yuankai K. Tao, Ipek Oguz

We then construct the local intensity fusion encoder (LIFE) to map a given OCT-A volume and its LIF counterpart to a shared latent space.

Retinal Vessel Segmentation

Graph Convolution for Re-ranking in Person Re-identification

1 code implementation5 Jul 2021 Yuqi Zhang, Qian Qi, Chong Liu, Weihua Chen, Fan Wang, Hao Li, Rong Jin

In this work, we propose a graph-based re-ranking method to improve learned features while still keeping Euclidean distance as the similarity metric.

Person Re-Identification Re-Ranking

Align Yourself: Self-supervised Pre-training for Fine-grained Recognition via Saliency Alignment

no code implementations30 Jun 2021 Di wu, Siyuan Li, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

In this paper, we first point out that current contrastive methods are prone to memorizing background/foreground texture and therefore have a limitation in localizing the foreground object.

Contrastive Learning Image Classification +1

Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement

no code implementations CVPR 2021 Huiwen Luo, Koki Nagano, Han-Wei Kung, Mclean Goldwhite, Qingguo Xu, Zejian Wang, Lingyu Wei, Liwen Hu, Hao Li

Cutting-edge 3D face reconstruction methods use non-linear morphable face models combined with GAN-based decoders to capture the likeness and details of a person but fail to produce neutral head models with unshaded albedo textures which is critical for creating relightable and animation-friendly avatars for integration in virtual environments.

3D Face Reconstruction Face Model

SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature

1 code implementation CVPR 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

Task-Generic Hierarchical Human Motion Prior using VAEs

no code implementations7 Jun 2021 Jiaman Li, Ruben Villegas, Duygu Ceylan, Jimei Yang, Zhengfei Kuang, Hao Li, Yajie Zhao

We demonstrate the effectiveness of our hierarchical motion variational autoencoder in a variety of tasks including video-based human pose estimation, motion completion from partial observations, and motion synthesis from sparse key-frames.

Frame motion synthesis +1

SKFAC:Training Neural Networks with Faster Kronecker-Factored Approximate Curvature

1 code implementation Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

KVT: k-NN Attention for Boosting Vision Transformers

no code implementations28 May 2021 Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin

A key component in vision transformers is the fully-connected self-attention which is more powerful than CNNs in modelling long range dependencies.

Unsupervised Visual Representation Learning by Online Constrained K-Means

1 code implementation24 May 2021 Qi Qian, Yuanhong Xu, Juhua Hu, Hao Li, Rong Jin

Clustering is to assign each instance a pseudo label that will be used to learn representations in discrimination.

Contrastive Learning Metric Learning +2

An Efficient Training Approach for Very Large Scale Face Recognition

1 code implementation21 May 2021 Kai Wang, Shuo Wang, Panpan Zhang, Zhipeng Zhou, Zheng Zhu, Xiaobo Wang, Xiaojiang Peng, Baigui Sun, Hao Li, Yang You

This method adopts Dynamic Class Pool (DCP) for storing and updating the identities features dynamically, which could be regarded as a substitute for the FC layer.

 Ranked #1 on Face Verification on IJB-C (dataset metric)

Face Recognition Face Verification

An Empirical Study of Vehicle Re-Identification on the AI City Challenge

1 code implementation20 May 2021 Hao Luo, Weihua Chen, Xianzhe Xu, Jianyang Gu, Yuqi Zhang, Chong Liu, Yiqi Jiang, Shuting He, Fan Wang, Hao Li

We mainly focus on four points, i. e. training data, unsupervised domain-adaptive (UDA) training, post-processing, model ensembling in this challenge.

Re-Ranking Vehicle Re-Identification

City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones

1 code implementation14 May 2021 Chong Liu, Yuqi Zhang, Hao Luo, Jiasheng Tang, Weihua Chen, Xianzhe Xu, Fan Wang, Hao Li, Yi-Dong Shen

Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions.

Vehicle Re-Identification

Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations

no code implementations14 May 2021 Xiaolong Fan, Maoguo Gong, Yue Wu, Hao Li

Specifically, we first utilize a multi-view representation learning module to better capture both local and global information content across feature and topology views on graphs.

Graph Representation Learning

Importance Weighted Adversarial Discriminative Transfer for Anomaly Detection

1 code implementation14 May 2021 Cangning Fan, Fangyi Zhang, Peng Liu, Xiuyu Sun, Hao Li, Ting Xiao, Wei Zhao, Xianglong Tang

In this way, an obvious gap can be produced between the distributions of normal and abnormal data in the target domain, therefore enabling the anomaly detection in the domain.

Anomaly Detection

Why Does Multi-Epoch Training Help?

no code implementations13 May 2021 Yi Xu, Qi Qian, Hao Li, Rong Jin

Stochastic gradient descent (SGD) has become the most attractive optimization method in training large-scale deep neural networks due to its simplicity, low computational cost in each updating step, and good performance.

Spatially Self-Paced Convolutional Networks for Change Detection in Heterogeneous Images

no code implementations IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 Hao Li, Maoguo Gong, Mingyang Zhang, Yue Wu

Change detection in heterogeneous remote sensing images is a challenging problem because it is hard to make a direct comparison in the original observation spaces, and most methods rely on a set of manually labeled samples.

Change Detection

Learning to Cluster Faces via Transformer

no code implementations23 Apr 2021 Jinxing Ye, Xioajiang Peng, Baigui Sun, Kai Wang, Xiuyu Sun, Hao Li, Hanqing Wu

In this paper, we repurpose the well-known Transformer and introduce a Face Transformer for supervised face clustering.

Face Clustering

A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation

1 code implementation ICCV 2021 Jianlong Yuan, Yifan Liu, Chunhua Shen, Zhibin Wang, Hao Li

Previous works [3, 27] fail to employ strong augmentation in pseudo label learning efficiently, as the large distribution change caused by strong augmentation harms the batch normalisation statistics.

Data Augmentation Image Classification +1

Spatiotemporal Entropy Model is All You Need for Learned Video Compression

1 code implementation13 Apr 2021 Zhenhong Sun, Zhiyu Tan, Xiuyu Sun, Fangyi Zhang, Dongyang Li, Yichen Qian, Hao Li

The framework of dominant learned video compression methods is usually composed of motion prediction modules as well as motion vector and residual image compression modules, suffering from its complex structure and error propagation problem.

Image Compression motion prediction +3

A Theoretical Analysis of Learning with Noisily Labeled Data

no code implementations8 Apr 2021 Yi Xu, Qi Qian, Hao Li, Rong Jin

Noisy labels are very common in deep supervised learning.

Augmented Transformer with Adaptive Graph for Temporal Action Proposal Generation

no code implementations30 Mar 2021 Shuning Chang, Pichao Wang, Fan Wang, Hao Li, Jiashi Feng

Temporal action proposal generation (TAPG) is a fundamental and challenging task in video understanding, especially in temporal action detection.

Action Detection Temporal Action Proposal Generation +1

Guided Training: A Simple Method for Single-channel Speaker Separation

no code implementations26 Mar 2021 Hao Li, Xueliang Zhang, Guanglai Gao

Another way is to use an anchor speech, a short speech of the target speaker, to model the speaker identity.

Speaker Separation Speech Separation

AutoLoss-Zero: Searching Loss Functions from Scratch for Generic Tasks

no code implementations25 Mar 2021 Hao Li, Tianwen Fu, Jifeng Dai, Hongsheng Li, Gao Huang, Xizhou Zhu

However, the automatic design of loss functions for generic tasks with various evaluation metrics remains under-investigated.

Equivariant Point Network for 3D Point Cloud Analysis

1 code implementation CVPR 2021 Haiwei Chen, Shichen Liu, Weikai Chen, Hao Li

Features that are equivariant to a larger group of symmetries have been shown to be more discriminative and powerful in recent studies.

PlenOctrees for Real-time Rendering of Neural Radiance Fields

3 code implementations ICCV 2021 Alex Yu, RuiLong Li, Matthew Tancik, Hao Li, Ren Ng, Angjoo Kanazawa

We introduce a method to render Neural Radiance Fields (NeRFs) in real time using PlenOctrees, an octree-based 3D representation which supports view-dependent effects.

Neural Rendering Novel View Synthesis

Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

1 code implementation CVPR 2021 Qiang Zhou, Chaohui Yu, Zhibin Wang, Qi Qian, Hao Li

To alleviate the confirmation bias problem and improve the quality of pseudo annotations, we further propose a co-rectify scheme based on Instant-Teaching, denoted as Instant-Teaching$^*$.

Object Detection Semi-Supervised Object Detection

MogFace: Towards a Deeper Appreciation on Face Detection

2 code implementations20 Mar 2021 Yang Liu, Fei Wang, Jiankang Deng, Zhipeng Zhou, Baigui Sun, Hao Li

As a result, practical solutions on label assignment, scale-level data augmentation, and reducing false alarms are necessary for advancing face detectors.

Data Augmentation Face Detection

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

1 code implementation1 Feb 2021 Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

Comparing with previous NAS methods, the proposed Zen-NAS is magnitude times faster on multiple server-side and mobile-side GPU platforms with state-of-the-art accuracy on ImageNet.

Image Classification Neural Architecture Search

Robust Representation Learning with Feedback for Single Image Deraining

1 code implementation CVPR 2021 Chenghao Chen, Hao Li

Unlike existing image deraining methods that embed low-quality features into the model directly, we replace low-quality features by latent high-quality features.

Representation Learning Single Image Deraining

A linearized framework and a new benchmark for model selection for fine-tuning

no code implementations29 Jan 2021 Aditya Deshpande, Alessandro Achille, Avinash Ravichandran, Hao Li, Luca Zancato, Charless Fowlkes, Rahul Bhotika, Stefano Soatto, Pietro Perona

Since all model selection algorithms in the literature have been tested on different use-cases and never compared directly, we introduce a new comprehensive benchmark for model selection comprising of: i) A model zoo of single and multi-domain models, and ii) Many target tasks.

Model Selection

Object Detection Made Simpler by Eliminating Heuristic NMS

no code implementations28 Jan 2021 Qiang Zhou, Chaohui Yu, Chunhua Shen, Zhibin Wang, Hao Li

On the COCO dataset, our simple design achieves superior performance compared to both the FCOS baseline detector with NMS post-processing and the recent end-to-end NMS-free detectors.

Object Detection

On w-Optimization of the Split Covariance Intersection Filter

no code implementations25 Jan 2021 Hao Li

The split covariance intersection filter (split CIF) is a useful tool for general data fusion and has the potential to be applied in a variety of engineering tasks.

1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking

1 code implementation20 Jan 2021 Fei Du, Bo Xu, Jiasheng Tang, Yuqi Zhang, Fan Wang, Hao Li

We extend the classical tracking-by-detection paradigm to this tracking-any-object task.

 Ranked #1 on Multi-Object Tracking on TAO (using extra training data)

Multi-Object Tracking

Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition

1 code implementation ICCV 2021 Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

To address this issue, instead of using an accuracy predictor, we propose a novel zero-shot index dubbed Zen-Score to rank the architectures.

Neural Architecture Search

Detection of magnetic gap in the topological surface states of MnBi2Te4

no code implementations31 Dec 2020 Haoran Ji, Yanzhao Liu, He Wang, Jiawei Luo, Jiaheng Li, Hao Li, Yang Wu, Yong Xu, Jian Wang

An essential ingredient to realize these quantum states is the magnetic gap in the topological surface states induced by the out-of-plane ferromagnetism on the surface of MnBi2Te4.

Materials Science

1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification

1 code implementation25 Dec 2020 Jianyang Gu, Hao Luo, Weihua Chen, Yiqi Jiang, Yuqi Zhang, Shuting He, Fan Wang, Hao Li, Wei Jiang

Considering the large gap between the source domain and target domain, we focused on solving two biases that influenced the performance on domain adaptive pedestrian Re-ID and proposed a two-stage training procedure.

Domain Adaptation

AsymptoticNG: A regularized natural gradient optimization algorithm with look-ahead strategy

no code implementations24 Dec 2020 Zedong Tang, Fenlong Jiang, Junke Song, Maoguo Gong, Hao Li, Fan Yu, Zidong Wang, Min Wang

Optimizers that further adjust the scale of gradient, such as Adam, Natural Gradient (NG), etc., despite widely concerned and used by the community, are often found poor generalization performance, compared with Stochastic Gradient Descent (SGD).

Amplifying the Anterior-Posterior Difference via Data Enhancement -- A More Robust Deep Monocular Orientation Estimation Solution

no code implementations21 Dec 2020 Chenchen Zhao, Hao Li

Existing deep-learning based monocular orientation estimation algorithms faces the problem of confusion between the anterior and posterior parts of the objects, caused by the feature similarity of such parts in typical objects in traffic scenes such as cars and pedestrians.

Decision Making

Blurring Fools the Network -- Adversarial Attacks by Feature Peak Suppression and Gaussian Blurring

no code implementations21 Dec 2020 Chenchen Zhao, Hao Li

Existing pixel-level adversarial attacks on neural networks may be deficient in real scenarios, since pixel-level changes on the data cannot be fully delivered to the neural network after camera capture and multiple image preprocessing steps.

Adversarial Attack

Exploiting Vulnerability of Pooling in Convolutional Neural Networks by Strict Layer-Output Manipulation for Adversarial Attacks

no code implementations21 Dec 2020 Chenchen Zhao, Hao Li

Then an attack method based on Strict Pooling Manipulation (SPM) which is an instantiation of the SLOM spirit is designed to effectively realize both type I and type II adversarial attacks on a target CNN.

Adversarial Attack Dimensionality Reduction

AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition

no code implementations18 Dec 2020 Kai Wang, Yuxin Gu, Xiaojiang Peng, Panpan Zhang, Baigui Sun, Hao Li

The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which pose an evident challenge for adapting the FER model trained on one dataset to another one.

Facial Expression Recognition

An Event Correlation Filtering Method for Fake News Detection

no code implementations10 Dec 2020 Hao Li, Huan Wang, Guanghua Liu

To improve the detection performance of fake news, we take advantage of the event correlations of news and propose an event correlation filtering method (ECFM) for fake news detection, mainly consisting of the news characterizer, the pseudo label annotator, the event credibility updater, and the news entropy selector.

Fake News Detection

Seed the Views: Hierarchical Semantic Alignment for Contrastive Representation Learning

no code implementations4 Dec 2020 Haohang Xu, Xiaopeng Zhang, Hao Li, Lingxi Xie, Hongkai Xiong, Qi Tian

In this paper, we propose a hierarchical semantic alignment strategy via expanding the views generated by a single image to \textbf{Cross-samples and Multi-level} representation, and models the invariance to semantically similar images in a hierarchical way.

Contrastive Learning Representation Learning +2

Arbitrary-Oriented Object Detection in Remote Sensing Images Based on Polar Coordinates

no code implementations IEEE Access 2020 Lin Zhou, Haoran Wei, Hao Li, Wenzhe Zhao, Yi Zhang, Yue Zhang

In this article, we introduce the polar coordinate system to the deep learning detector for the first time, and propose an anchor free Polar Remote Sensing Object Detector (P-RSDet), which can achieve competitive detection accuracy via using simpler object representation model and less regression parameters.

Object Detection One-stage Anchor-free Oriented Object Detection

Heterogeneous Contrastive Learning: Encoding Spatial Information for Compact Visual Representations

no code implementations19 Nov 2020 Xinyue Huo, Lingxi Xie, Longhui Wei, Xiaopeng Zhang, Hao Li, Zijie Yang, Wengang Zhou, Houqiang Li, Qi Tian

Contrastive learning has achieved great success in self-supervised visual representation learning, but existing approaches mostly ignored spatial information which is often crucial for visual representation.

Contrastive Learning Data Augmentation +1

ULSD: Unified Line Segment Detection across Pinhole, Fisheye, and Spherical Cameras

2 code implementations6 Nov 2020 Hao Li, Huai Yu, Wen Yang, Lei Yu, Sebastian Scherer

Targeting at the unified line segment detection (ULSD) for both distorted and undistorted images, we propose to represent line segments with the Bezier curve model.

Line Segment Detection

Center-wise Local Image Mixture For Contrastive Representation Learning

no code implementations5 Nov 2020 Hao Li, Xiaopeng Zhang, Hongkai Xiong

Contrastive learning based on instance discrimination trains model to discriminate different transformations of the anchor sample from other samples, which does not consider the semantic similarity among samples.

Contrastive Learning Data Augmentation +3

Data Augmentation for End-to-end Code-switching Speech Recognition

no code implementations4 Nov 2020 Chenpeng Du, Hao Li, Yizhou Lu, Lan Wang, Yanmin Qian

Training a code-switching end-to-end automatic speech recognition (ASR) model normally requires a large amount of data, while code-switching data is often limited.

Automatic Speech Recognition Data Augmentation +2

Speakerfilter-Pro: an improved target speaker extractor combines the time domain and frequency domain

no code implementations25 Oct 2020 Shulin He, Hao Li, Xueliang Zhang

This paper introduces an improved target speaker extractor, referred to as Speakerfilter-Pro, based on our previous Speakerfilter model.

Speech Separation

Learning Accurate Entropy Model with Global Reference for Image Compression

2 code implementations ICLR 2021 Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin

In this work, we propose a novel Global Reference Model for image compression to effectively leverage both the local and the global context information, leading to an enhanced compression rate.

Image Compression

Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation

1 code implementation ICLR 2021 Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai

In this paper, we propose to automate the design of metric-specific loss functions by searching differentiable surrogate losses for each metric.

Semantic Segmentation

Domain Agnostic Learning for Unbiased Authentication

no code implementations11 Oct 2020 Jian Liang, Yuren Cao, Shuang Li, Bing Bai, Hao Li, Fei Wang, Kun Bai

We further extend our method to a meta-learning framework to pursue more thorough domain-difference elimination.

Face Recognition Meta-Learning +1

Position-Aware Tagging for Aspect Sentiment Triplet Extraction

4 code implementations EMNLP 2020 Lu Xu, Hao Li, Wei Lu, Lidong Bing

Our observation is that the three elements within a triplet are highly related to each other, and this motivates us to build a joint model to extract such triplets using a sequence tagging approach.

Aspect Sentiment Triplet Extraction

WeMix: How to Better Utilize Data Augmentation

no code implementations3 Oct 2020 Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin

To this end, we develop two novel algorithms, termed "AugDrop" and "MixLoss", to correct the data bias in the data augmentation.

Data Augmentation

Dynamic Facial Asset and Rig Generation from a Single Scan

no code implementations1 Oct 2020 Jiaman Li, Zheng-Fei Kuang, Yajie Zhao, Mingming He, Karl Bladin, Hao Li

We also model the joint distribution between identities and expressions, enabling the inference of the full set of personalized blendshapes with dynamic appearances from a single neutral input scan.

Improved Knowledge Distillation via Full Kernel Matrix Transfer

1 code implementation30 Sep 2020 Qi Qian, Hao Li, Juhua Hu

Recently, a number of works propose to transfer the pairwise similarity between examples to distill relative information.

Knowledge Distillation Model Compression

Semi-Anchored Detector for One-Stage Object Detection

no code implementations10 Sep 2020 Lei Chen, Qi Qian, Hao Li

The anchor-free strategy benefits the classification task but can lead to sup-optimum for the regression task due to the lack of prior bounding boxes.

Classification General Classification +1

Hybrid Differentially Private Federated Learning on Vertically Partitioned Data

no code implementations6 Sep 2020 Chang Wang, Jian Liang, Mingkai Huang, Bing Bai, Kun Bai, Hao Li

We present HDP-VFL, the first hybrid differentially private (DP) framework for vertical federated learning (VFL) to demonstrate that it is possible to jointly learn a generalized linear model (GLM) from vertically partitioned data with only a negligible cost, w. r. t.

Federated Learning

A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations

no code implementations25 Aug 2020 Mingkai Huang, Hao Li, Bing Bai, Chang Wang, Kun Bai, Fei Wang

Federated Learning(FL) is a newly developed privacy-preserving machine learning paradigm to bridge data repositories without compromising data security and privacy.

Collaborative Filtering Federated Learning

Stochastic scattering theory for excitation induced dephasing: Comparison to the Anderson-Kubo lineshape

no code implementations20 Aug 2020 Hao Li, Ajay Ram Srimath Kandada, Carlos Silva, Eric R. Bittner

In this paper we present a quantum stochastic model for spectroscopic line-shapes in the presence of a co-evolving and non-stationary background population of excitations.

Chemical Physics Mesoscale and Nanoscale Physics

Learning to Generate Diverse Dance Motions with Transformer

no code implementations18 Aug 2020 Jiaman Li, Yihang Yin, Hang Chu, Yi Zhou, Tingwu Wang, Sanja Fidler, Hao Li

We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods.

motion synthesis

Monocular Real-Time Volumetric Performance Capture

1 code implementation ECCV 2020 Ruilong Li, Yuliang Xiu, Shunsuke Saito, Zeng Huang, Kyle Olszewski, Hao Li

We present the first approach to volumetric performance capture and novel-view rendering at real-time speed from monocular video, eliminating the need for expensive multi-view systems or cumbersome pre-acquisition of a personalized template model.

3D Human Shape Estimation

Posterior Consistency of Semi-Supervised Regression on Graphs

no code implementations25 Jul 2020 Andrea L. Bertozzi, Bamdad Hosseini, Hao Li, Kevin Miller, Andrew M. Stuart

Graph-based semi-supervised regression (SSR) is the problem of estimating the value of a function on a weighted graph from its values (labels) on a small subset of the vertices.

Efficient Graph-Based Active Learning with Probit Likelihood via Gaussian Approximations

no code implementations21 Jul 2020 Kevin Miller, Hao Li, Andrea L. Bertozzi

We present a novel adaptation of active learning to graph-based semi-supervised learning (SSL) under non-Gaussian Bayesian models.

Active Learning

Neural Architecture Design for GPU-Efficient Networks

2 code implementations24 Jun 2020 Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

To address this issue, we propose a general principle for designing GPU-efficient networks based on extensive empirical studies.

Neural Architecture Search

Towards Understanding Label Smoothing

no code implementations20 Jun 2020 Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin

Label smoothing regularization (LSR) has a great success in training deep neural networks by stochastic algorithms such as stochastic gradient descent and its variants.

Revisiting the Continuity of Rotation Representations in Neural Networks

no code implementations11 Jun 2020 Sitao Xiang, Hao Li

In this paper, we provide some careful analysis of certain pathological behavior of Euler angles and unit quaternions encountered in previous works related to rotation representation in neural networks.

Why Attentions May Not Be Interpretable?

no code implementations10 Jun 2020 Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang

In this paper, we demonstrate that one root cause of this phenomenon is the combinatorial shortcuts, which means that, in addition to the highlighted parts, the attention weights themselves may carry extra information that could be utilized by downstream models after attention layers.

Feature Importance

Weakly Supervised Representation Learning with Coarse Labels

1 code implementation ICCV 2021 Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu

To mitigate this challenge, we propose an algorithm to learn the fine-grained patterns for the target task, when only its coarse-class labels are available.

Representation Learning

Generative Tweening: Long-term Inbetweening of 3D Human Motions

no code implementations18 May 2020 Yi Zhou, Jingwan Lu, Connelly Barnes, Jimei Yang, Sitao Xiang, Hao Li

We introduce a biomechanically constrained generative adversarial network that performs long-term inbetweening of human motions, conditioned on keyframe constraints.

One-Shot Identity-Preserving Portrait Reenactment

no code implementations26 Apr 2020 Sitao Xiang, Yuming Gu, Pengda Xiang, Mingming He, Koki Nagano, Haiwei Chen, Hao Li

This is achieved by a novel landmark disentanglement network (LD-Net), which predicts personalized facial landmarks that combine the identity of the target with expressions and poses from a different subject.


Lightweight Mask R-CNN for Long-Range Wireless Power Transfer Systems

no code implementations19 Apr 2020 Hao Li, Aozhou Wu, Wen Fang, Qingqing Zhang, Mingqing Liu, Qingwen Liu, Wei Chen

The proposed approach makes the object detection much easier to be transplanted on mobile devices and reduce the burden of hardware computation.

Object Detection

Intuitive, Interactive Beard and Hair Synthesis with Generative Models

1 code implementation CVPR 2020 Kyle Olszewski, Duygu Ceylan, Jun Xing, Jose Echevarria, Zhili Chen, Weikai Chen, Hao Li

We present an interactive approach to synthesizing realistic variations in facial hair in images, ranging from subtle edits to existing hair to the addition of complex and challenging hair in images of clean-shaven subjects.

ARCH: Animatable Reconstruction of Clothed Humans

no code implementations CVPR 2020 Zeng Huang, Yuanlu Xu, Christoph Lassner, Hao Li, Tony Tung

In this paper, we propose ARCH (Animatable Reconstruction of Clothed Humans), a novel end-to-end framework for accurate reconstruction of animation-ready 3D clothed humans from a monocular image.

3D Object Reconstruction From A Single Image 3D Reconstruction

CSRN: Collaborative Sequential Recommendation Networks for News Retrieval

no code implementations7 Apr 2020 Bing Bai, Guanhua Zhang, Ye Lin, Hao Li, Kun Bai, Bo Luo

Recurrent Neural Network (RNN)-based sequential recommendation is a popular approach that utilizes users' recent browsing history to predict future items.

Collaborative Filtering News Retrieval +1

Learning Formation of Physically-Based Face Attributes

no code implementations CVPR 2020 Ruilong Li, Karl Bladin, Yajie Zhao, Chinmay Chinara, Owen Ingraham, Pengda Xiang, Xinglei Ren, Pratusha Prasad, Bipin Kishore, Jun Xing, Hao Li

Based on a combined data set of 4000 high resolution facial scans, we introduce a non-linear morphable face model, capable of producing multifarious face geometry of pore-level resolution, coupled with material attributes for use in physically-based rendering.

Data Visualization Face Model

Rethinking the Hyperparameters for Fine-tuning

1 code implementation ICLR 2020 Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

Our findings challenge common practices of fine-tuning and encourages deep learning practitioners to rethink the hyperparameters for fine-tuning.

Transfer Learning

Objects detection for remote sensing images based on polar coordinates

no code implementations9 Jan 2020 Lin Zhou, Hao-Ran Wei, Hao Li, Wenzhe Zhao, Yi Zhang, Yue Zhang

In this article, we introduce the polar coordinate system to the deep learning detector for the first time, and propose an anchor free Polar Remote Sensing Object Detector (P-RSDet), which can achieve competitive detection accuracy via uses simpler object representation model and less regression parameters.

Object Detection

So2Sat LCZ42: A Benchmark Dataset for Global Local Climate Zones Classification

1 code implementation19 Dec 2019 Xiao Xiang Zhu, Jingliang Hu, Chunping Qiu, Yilei Shi, Jian Kang, Lichao Mou, Hossein Bagheri, Matthias Häberle, Yuansheng Hua, Rong Huang, Lloyd Hughes, Hao Li, Yao Sun, Guichen Zhang, Shiyao Han, Michael Schmitt, Yuanyuan Wang

This is especially true for an automated analysis of remote sensing images on a global scale, which enables us to address global challenges such as urbanization and climate change using state-of-the-art machine learning techniques.

General Classification

Hierarchically Robust Representation Learning

no code implementations CVPR 2020 Qi Qian, Juhua Hu, Hao Li

Experiments on benchmark data sets demonstrate the effectiveness of the robust deep representations.

Representation Learning

Learning to Infer Implicit Surfaces without 3D Supervision

no code implementations NeurIPS 2019 Shichen Liu, Shunsuke Saito, Weikai Chen, Hao Li

The representation of 3D surfaces itself is a key factor for the quality and resolution of the 3D output.

3D Shape Generation

Learning Explicit and Implicit Structures for Targeted Sentiment Analysis

no code implementations IJCNLP 2019 Hao Li, Wei Lu

In this work, we argue that both types of information (implicit and explicit structural information) are crucial for building a successful targeted sentiment analysis model.

Sentiment Analysis

Improved Techniques for Training Adaptive Deep Networks

1 code implementation ICCV 2019 Hao Li, Hong Zhang, Xiaojuan Qi, Ruigang Yang, Gao Huang

Adaptive inference is a promising technique to improve the computational efficiency of deep models at test time.

Knowledge Distillation

X-LineNet: Detecting Aircraft in Remote Sensing Images by a pair of Intersecting Line Segments

no code implementations29 Jul 2019 Hao-Ran Wei, Yue Zhang, Bing Wang, Yang Yang, Hao Li, Hongqi Wang

Motivated by the development of deep convolution neural networks (DCNNs), tremendous progress has been gained in the field of aircraft detection.

Reinforced Dynamic Reasoning for Conversational Question Generation

1 code implementation ACL 2019 Boyuan Pan, Hao Li, Ziyu Yao, Deng Cai, Huan Sun

This paper investigates a new task named Conversational Question Generation (CQG) which is to generate a question based on a passage and a conversation history (i. e., previous turns of question-answer pairs).

Question Answering Question Generation

DR Loss: Improving Object Detection by Distributional Ranking

1 code implementation CVPR 2020 Qi Qian, Lei Chen, Hao Li, Rong Jin

This architecture is efficient but can suffer from the imbalance issue with respect to two aspects: the inter-class imbalance between the number of candidates from foreground and background classes and the intra-class imbalance in the hardness of background candidates, where only a few candidates are hard to be identified.

Object Detection

HPILN: A feature learning framework for cross-modality person re-identification

no code implementations7 Jun 2019 Jian-Wu Lin, Hao Li

Most video surveillance systems use both RGB and infrared cameras, making it a vital technique to re-identify a person cross the RGB and infrared modalities.

Cross-Modality Person Re-identification Person Re-Identification

Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

no code implementations3 Jun 2019 Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin

We validate the superiority of the proposed method in our real-time high precision positioning system against several popular state-of-the-art robust regression methods.


Neural Chinese Address Parsing

no code implementations NAACL 2019 Hao Li, Wei Lu, Pengjun Xie, Linlin Li

This paper introduces a new task {--} Chinese address parsing {--} the task of mapping Chinese addresses into semantically meaningful chunks.

Structured Prediction

Disentangling Style and Content in Anime Illustrations

no code implementations26 May 2019 Sitao Xiang, Hao Li

We propose a novel Generative Adversarial Disentanglement Network which can disentangle two complementary factors of variations when only one of them is labelled in general, and fully decompose complex anime illustrations into style and content in particular.

Disentanglement Style Transfer

Learning Perspective Undistortion of Portraits

no code implementations ICCV 2019 Yajie Zhao, Zeng Huang, Tianye Li, Weikai Chen, Chloe LeGendre, Xinglei Ren, Jun Xing, Ari Shapiro, Hao Li

In contrast to the previous state-of-the-art approach, our method handles even portraits with extreme perspective distortion, as we avoid the inaccurate and error-prone step of first fitting a 3D face model.

3D Reconstruction Camera Calibration +2

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

1 code implementation ICCV 2019 Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, Hao Li

We introduce Pixel-aligned Implicit Function (PIFu), a highly effective implicit representation that locally aligns pixels of 2D images with the global context of their corresponding 3D object.

3D Human Pose Estimation 3D Human Reconstruction +2

Semi-Supervised First-Person Activity Recognition in Body-Worn Video

no code implementations19 Apr 2019 Honglin Chen, Hao Li, Alexander Song, Matt Haberland, Osman Akar, Adam Dhillon, Tiankuang Zhou, Andrea L. Bertozzi, P. Jeffrey Brantingham

Body-worn cameras are now commonly used for logging daily life, sports, and law enforcement activities, creating a large volume of archived footage.

Activity Recognition

Transformable Bottleneck Networks

1 code implementation ICCV 2019 Kyle Olszewski, Sergey Tulyakov, Oliver Woodford, Hao Li, Linjie Luo

We propose a novel approach to performing fine-grained 3D manipulation of image content via a convolutional neural network, which we call the Transformable Bottleneck Network (TBN).

3D Reconstruction Novel View Synthesis

Pancreas segmentation with probabilistic map guided bi-directional recurrent UNet

no code implementations3 Mar 2019 Jun Li, Xiaozhu Lin, Hui Che, Hao Li, Xiaohua Qian

To alleviate these problems, we propose a probabilistic-map-guided bi-directional recurrent UNet (PBR-UNet) architecture, which fuses intra-slice information and inter-slice probabilistic maps into a local 3D hybrid regularization scheme, which is followed by bi-directional recurrent network optimization.

Pancreas Segmentation

A Model-Driven Stack-Based Fully Convolutional Network for Pancreas Segmentation

no code implementations3 Mar 2019 Hao Li, Jun Li, Xiaozhu Lin, Xiaohua Qian

The irregular geometry and high inter-slice variability in computerized tomography (CT) scans of the human pancreas make an accurate segmentation of this crucial organ a challenging task for existing data-driven deep learning methods.

Pancreas Segmentation

Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction

no code implementations17 Jan 2019 Shichen Liu, Weikai Chen, Tianye Li, Hao Li

We also show that our soft rasterizer can achieve comparable results to the cutting-edge supervised learning method and in various cases even better ones, especially for real-world data.

SiCloPe: Silhouette-Based Clothed People

no code implementations CVPR 2019 Ryota Natsume, Shunsuke Saito, Zeng Huang, Weikai Chen, Chongyang Ma, Hao Li, Shigeo Morishima

The synthesized silhouettes which are the most consistent with the input segmentation are fed into a deep visual hull algorithm for robust 3D shape prediction.

Image-to-Image Translation

On the Continuity of Rotation Representations in Neural Networks

5 code implementations CVPR 2019 Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, Hao Li

Thus, widely used representations such as quaternions and Euler angles are discontinuous and difficult for neural networks to learn.

Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions

no code implementations11 Dec 2018 Weikai Chen, Xiaoguang Han, Guanbin Li, Chao Chen, Jun Xing, Yajie Zhao, Hao Li

Three-dimensional object recognition has recently achieved great progress thanks to the development of effective point cloud-based learning frameworks, such as PointNet and its extensions.

3D Object Recognition

Multivariate Spatiotemporal Hawkes Processes and Network Reconstruction

no code implementations15 Nov 2018 Baichuan Yuan, Hao Li, Andrea L. Bertozzi, P. Jeffrey Brantingham, Mason A. Porter

There is often latent network structure in spatial and temporal data and the tools of network analysis can yield fascinating insights into such data.

Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data

no code implementations1 Nov 2018 Hao Li, Yang Wang, Xinyu Liu, Zhichao Sheng, Si Wei

We propose a nested recurrent neural network (nested RNN) model for English spelling error correction and generate pseudo data based on phonetic similarity to train it.

Feature Engineering

Deep Volumetric Video From Very Sparse Multi-View Performance Capture

no code implementations ECCV 2018 Zeng Huang, Tianye Li, Weikai Chen, Yajie Zhao, Jun Xing, Chloe LeGendre, Linjie Luo, Chongyang Ma, Hao Li

We present a deep learning-based volumetric capture approach for performance capture using a passive and highly sparse multi-view capture system.

Frame Surface Reconstruction

Real-Time Hair Rendering using Sequential Adversarial Networks

no code implementations ECCV 2018 Lingyu Wei, Liwen Hu, Vladimir Kim, Ersin Yumer, Hao Li

To handle the diversity of hairstyles and its appearance complexity, we disentangle hair structure, color, and illumination properties using a sequential GAN architecture and a semi-supervised training approach.