Search Results for author: Chao Li

Found 192 papers, 74 papers with code

Evolutionary Topology Search for Tensor Network Decomposition

no code implementations ICML 2020 Chao Li, Zhun Sun

Tensor network (TN) decomposition is a promising framework to represent extremely high-dimensional problems with few parameters.

Evolutionary Algorithms

Cross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics

no code implementations19 Apr 2024 Xiaofei Wang, Xingxu Huang, Stephen J. Price, Chao Li

However, current ST platforms suffer from low resolution, hindering in-depth understanding of spatial gene expression.

Super-Resolution

Idea-2-3D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs

1 code implementation5 Apr 2024 JunHao Chen, Xiang Li, Xiaojun Ye, Chao Li, Zhaoxin Fan, Hao Zhao

The definition of an IDEA is the composition of multimodal inputs including text, image, and 3D models.

Model Selection

Yi: Open Foundation Models by 01.AI

1 code implementation7 Mar 2024 01. AI, :, Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Heng Li, Jiangcheng Zhu, Jianqun Chen, Jing Chang, Kaidong Yu, Peng Liu, Qiang Liu, Shawn Yue, Senbin Yang, Shiming Yang, Tao Yu, Wen Xie, Wenhao Huang, Xiaohui Hu, Xiaoyi Ren, Xinyao Niu, Pengcheng Nie, Yuchi Xu, Yudong Liu, Yue Wang, Yuxuan Cai, Zhenyu Gu, Zhiyuan Liu, Zonghong Dai

The Yi model family is based on 6B and 34B pretrained language models, then we extend them to chat models, 200K long context models, depth-upscaled models, and vision-language models.

Attribute Chatbot +2

Data-efficient Event Camera Pre-training via Disentangled Masked Modeling

no code implementations1 Mar 2024 Zhenpeng Huang, Chao Li, Hao Chen, Yongjian Deng, Yifeng Geng, LiMin Wang

Our pre-training overcomes the limitations of previous methods, which either sacrifice temporal information by converting event sequences into 2D images for utilizing pre-trained image models or directly employ paired image data for knowledge distillation to enhance the learning of event streams.

Knowledge Distillation Self-Supervised Learning

Aligning Knowledge Graph with Visual Perception for Object-goal Navigation

1 code implementation29 Feb 2024 Nuo Xu, Wen Wang, Rong Yang, Mengjie Qin, Zheyuan Lin, Wei Song, Chunlong Zhang, Jason Gu, Chao Li

Object-goal navigation is a challenging task that requires guiding an agent to specific objects based on first-person visual observations.

Object

Discovering More Effective Tensor Network Structure Search Algorithms via Large Language Models (LLMs)

no code implementations4 Feb 2024 Junhua Zeng, Guoxu Zhou, Chao Li, Zhun Sun, Qibin Zhao

Tensor network structure search (TN-SS), aiming at searching for suitable tensor network (TN) structures in representing high-dimensional problems, largely promotes the efficacy of TN in various machine learning applications.

Image Compression

NOAH: Learning Pairwise Object Category Attentions for Image Classification

1 code implementation4 Feb 2024 Chao Li, Aojun Zhou, Anbang Yao

We observe that the head structures of mainstream DNNs adopt a similar feature encoding pipeline, exploiting global feature dependencies while disregarding local ones.

Classification Multi-Label Image Classification +1

A Polarization and Radiomics Feature Fusion Network for the Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma

no code implementations27 Dec 2023 Jia Dong, Yao Yao, Liyan Lin, Yang Dong, Jiachen Wan, Ran Peng, Chao Li, Hui Ma

Our experimental results underscore the potential of this fusion network as a powerful tool for computer-aided diagnosis of HCC and ICC, showcasing the benefits and prospects of integrating polarization imaging techniques into the current image-intensive digital pathological diagnosis.

Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation

1 code implementation7 Dec 2023 Jiawei Fan, Chao Li, Xiaolong Liu, Meina Song, Anbang Yao

In order to address this problem, we present Augmentation-free Dense Contrastive Knowledge Distillation (Af-DCD), a new contrastive distillation learning paradigm to train compact and accurate deep neural networks for semantic segmentation applications.

Contrastive Learning Data Augmentation +6

BCN: Batch Channel Normalization for Image Classification

1 code implementation1 Dec 2023 Afifa Khaled, Chao Li, Jia Ning, Kun He

Normalization techniques have been widely used in the field of deep learning due to their capability of enabling higher learning rates and are less careful in initialization.

Classification Image Classification

4K-Resolution Photo Exposure Correction at 125 FPS with ~8K Parameters

1 code implementation15 Nov 2023 Yijie Zhou, Chao Li, Jin Liang, Tianyi Xu, Xin Liu, Jun Xu

The illumination of improperly exposed photographs has been widely corrected using deep convolutional neural networks or Transformers.

4k 8k

Feature Space Renormalization for Semi-supervised Learning

no code implementations7 Nov 2023 Jun Sun, Zhongjie Mao, Chao Li, Chao Zhou, Xiao-Jun Wu

The common framework among recent approaches is to train the model on a large amount of unlabelled data with consistency regularization to constrain the model predictions to be invariant to input perturbation.

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization

1 code implementation NeurIPS 2023 Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang

Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks.

Multi-agent Reinforcement Learning reinforcement-learning

Exploring Data Augmentations on Self-/Semi-/Fully- Supervised Pre-trained Models

no code implementations28 Oct 2023 Shentong Mo, Zhun Sun, Chao Li

Data augmentation has become a standard component of vision pre-trained models to capture the invariance between augmented views.

Data Augmentation Image Classification +4

Asca: less audio data is more insightful

1 code implementation23 Sep 2023 Xiang Li, JunHao Chen, Chao Li, Hongwu Lv

Audio recognition in specialized areas such as birdsong and submarine acoustics faces challenges in large-scale pre-training due to the limitations in available samples imposed by sampling environments and specificity requirements.

Specificity

KernelWarehouse: Towards Parameter-Efficient Dynamic Convolution

1 code implementation16 Aug 2023 Chao Li, Anbang Yao

Dynamic convolution learns a linear mixture of $n$ static kernels weighted with their sample-dependent attentions, demonstrating superior performance compared to normal convolution.

Analyzing and controlling diversity in quantum-behaved particle swarm optimization

no code implementations9 Aug 2023 Li-Wei Li, Jun Sun, Chao Li, Wei Fang, Vasile Palade, Xiao-Jun Wu

Then, the correlations between the two types of diversities and the search performance are tested and analyzed on several benchmark functions, and the distance-to-average-point diversity is showed to have stronger association with the search performance during the evolving processes.

Long-range Meta-path Search on Large-scale Heterogeneous Graphs

3 code implementations17 Jul 2023 Chao Li, Zijie Guo, Qiuting He, Hao Xu, Kun He

To this end, we investigate the importance of different meta-paths and introduce an automatic framework for utilizing long-range dependency on heterogeneous graphs, denoted as Long-range Meta-path Search through Progressive Sampling (LMSPS).

Node Classification Node Property Prediction

RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World

1 code implementation ICCV 2023 Donghua Wang, Wen Yao, Tingsong Jiang, Chao Li, Xiaoqian Chen

In this paper, we propose a novel Reflected Light Attack (RFLA), featuring effective and stealthy in both the digital and physical world, which is implemented by placing the color transparent plastic sheet and a paper cut of a specific shape in front of the mirror to create different colored geometries on the target object.

Adversarial Attack Object

Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks

no code implementations14 Jul 2023 Chaoyu Liu, Zhonghua Qiao, Chao Li, Carola-Bibiane Schönlieb

These layers can achieve specific regularization objectives and endow neural networks' outputs with corresponding properties of the evolution models.

Semantic Segmentation

GroundNLQ @ Ego4D Natural Language Queries Challenge 2023

1 code implementation27 Jun 2023 Zhijian Hou, Lei Ji, Difei Gao, Wanjun Zhong, Kun Yan, Chao Li, Wing-Kwong Chan, Chong-Wah Ngo, Nan Duan, Mike Zheng Shou

Motivated by this, we leverage a two-stage pre-training strategy to train egocentric feature extractors and the grounding model on video narrations, and further fine-tune the model on annotated data.

Natural Language Queries

Adaptive Contextual Biasing for Transducer Based Streaming Speech Recognition

no code implementations1 Jun 2023 Tianyi Xu, Zhanheng Yang, Kaixun Huang, Pengcheng Guo, Ao Zhang, Biao Li, Changru Chen, Chao Li, Lei Xie

By incorporating additional contextual information, deep biasing methods have emerged as a promising solution for speech recognition of personalized words.

speech-recognition Speech Recognition

A Novel Driver Distraction Behavior Detection Method Based on Self-supervised Learning with Masked Image Modeling

1 code implementation1 Jun 2023 Yingzhi Zhang, Taiguo Li, Chao Li, Xinghong Zhou

In order to solve these problems, this paper proposes a new self-supervised learning method based on masked image modeling for driver distraction behavior detection.

Data Augmentation Self-Supervised Learning

SVDinsTN: A Tensor Network Paradigm for Efficient Structure Search from Regularized Modeling Perspective

no code implementations24 May 2023 Yu-Bang Zheng, Xi-Le Zhao, Junhua Zeng, Chao Li, Qibin Zhao, Heng-Chao Li, Ting-Zhu Huang

To address this issue, we propose a novel TN paradigm, named SVD-inspired TN decomposition (SVDinsTN), which allows us to efficiently solve the TN-SS problem from a regularized modeling perspective, eliminating the repeated structure evaluations.

NORM: Knowledge Distillation via N-to-One Representation Matching

1 code implementation23 May 2023 Xiaolong Liu, Lujun Li, Chao Li, Anbang Yao

By sequentially splitting the expanded student representation into N non-overlapping feature segments having the same number of feature channels as the teacher's, they can be readily forced to approximate the intact teacher representation simultaneously, formulating a novel many-to-one representation matching mechanism conditioned on a single teacher-student layer pair.

Knowledge Distillation

Impact of Light and Shadow on Robustness of Deep Neural Networks

no code implementations23 May 2023 Chengyin Hu, Weiwen Shi, Chao Li, Jialiang Sun, Donghua Wang, Junqi Wu, Guijian Tang

Deep neural networks (DNNs) have made remarkable strides in various computer vision tasks, including image classification, segmentation, and object detection.

Image Classification object-detection +1

Physics-based network fine-tuning for robust quantitative susceptibility mapping from high-pass filtered phase

no code implementations5 May 2023 Jinwei Zhang, Alexey Dimov, Chao Li, Hang Zhang, Thanh D. Nguyen, Pascal Spincemaille, Yi Wang

Purpose: To improve the generalization ability of convolutional neural network (CNN) based prediction of quantitative susceptibility mapping (QSM) from high-pass filtered phase (HPFP) image.

SSIM

Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations

1 code implementation25 Apr 2023 Chao Li, Junhua Zeng, Chunmei Li, Cesar Caiafa, Qibin Zhao

Tensor network (TN) is a powerful framework in machine learning, but selecting a good TN model, known as TN structure search (TN-SS), is a challenging and computationally intensive task.

Computational Efficiency

Meta-multigraph Search: Rethinking Meta-structure on Heterogeneous Information Networks

no code implementations23 Apr 2023 Chao Li, Hao Xu, Kun He

Meta-structures are widely used to define which subset of neighbors to aggregate information in heterogeneous information networks (HINs).

Node Classification

Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense

no code implementations14 Apr 2023 Jingyuan Wang, Yufan Wu, Mingxuan Li, Xin Lin, Junjie Wu, Chao Li

While having achieved great success in rich real-life applications, deep neural network (DNN) models have long been criticized for their vulnerability to adversarial attacks.

mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous quantitative multi-parametric mapping

no code implementations7 Apr 2023 Jinwei Zhang, Thanh D. Nguyen, Eddy Solomon, Chao Li, Qihao Zhang, Jiahao Li, Hang Zhang, Pascal Spincemaille, Yi Wang

Results: The retrospective ablation study showed improved image sharpness of mcLARO compared to the baseline network without multi-contrast sampling pattern optimization or image feature fusion, and negligible bias and narrow 95% limits of agreement on regional T1, T2, T2* and QSM values were obtained by the under-sampled reconstructions compared to the fully sampled reconstruction.

Image Reconstruction

Multi-task Learning of Histology and Molecular Markers for Classifying Diffuse Glioma

no code implementations26 Mar 2023 Xiaofei Wang, Stephen Price, Chao Li

This paper presents a first attempt to jointly predict molecular markers and histology features and model their interactions for classifying diffuse glioma bases on whole slide images.

Multi-Task Learning whole slide images

CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis

no code implementations24 Mar 2023 Lan Jiang, Ye Mao, Xi Chen, Xiangfeng Wang, Chao Li

Diffusion model has emerged as an effective technique for image synthesis by modelling complex and variable data distributions.

CoLA Image Generation

DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution

1 code implementation24 Mar 2023 Ye Mao, Lan Jiang, Xi Chen, Chao Li

Moreover, DisC-Diff leverages a disentangled multi-stream network to fully exploit complementary information from multi-contrast MRI, improving model interpretation under multiple conditions of multi-contrast inputs.

Image Enhancement Management +1

Practice of the conformer enhanced AUDIO-VISUAL HUBERT on Mandarin and English

no code implementations28 Feb 2023 Xiaoming Ren, Chao Li, Shenjian Wang, Biao Li

Considering the bimodal nature of human speech perception, lips, and teeth movement has a pivotal role in automatic speech recognition.

Automatic Speech Recognition speech-recognition +1

GMConv: Modulating Effective Receptive Fields for Convolutional Kernels

no code implementations9 Feb 2023 Qi Chen, Chao Li, Jia Ning, Stephen Lin, Kun He

Inspired by the property that ERFs typically exhibit a Gaussian distribution, we propose a Gaussian Mask convolutional kernel (GMConv) in this work.

Image Classification object-detection +1

Improved Differential-neural Cryptanalysis for Round-reduced Simeck32/64

no code implementations27 Jan 2023 Liu Zhang, Jinyu Lu, Zilong Wang, Chao Li

Inspired by this framework, we develop the Inception neural network that is compatible with the round function of Simeck to improve the accuracy of the neural distinguishers, thus improving the accuracy of (9-12)-round neural distinguishers for Simeck32/64.

Cryptanalysis

Spatially Covariant Lesion Segmentation

no code implementations19 Jan 2023 Hang Zhang, Rongguang Wang, Jinwei Zhang, Dongdong Liu, Chao Li, Jiahao Li

Compared to natural images, medical images usually show stronger visual patterns and therefore this adds flexibility and elasticity to resource-limited clinical applications by injecting proper priors into neural networks.

Computational Efficiency Lesion Segmentation +2

Centralized Cooperative Exploration Policy for Continuous Control Tasks

1 code implementation6 Jan 2023 Chao Li, Chen Gong, Qiang He, Xinwen Hou, Yu Liu

To explicitly encourage exploration in continuous control tasks, we propose CCEP (Centralized Cooperative Exploration Policy), which utilizes underestimation and overestimation of value functions to maintain the capacity of exploration.

Continuous Control

Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View

no code implementations ICCV 2023 Kelu Yao, Jin Wang, Boyu Diao, Chao Li

Deepfake detectors encode multi-order interactions among visual concepts, in which the low-order interactions usually have substantially negative contributions to deepfake detection.

DeepFake Detection Face Swapping

FDViT: Improve the Hierarchical Architecture of Vision Transformer

no code implementations ICCV 2023 Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao

In this paper, we propose FDViT to improve the hierarchical architecture of the vision transformer by using a flexible downsampling layer that is not limited to integer stride to smoothly reduce the sizes of the middle feature maps.

Accelerating Self-Imitation Learning from Demonstrations via Policy Constraints and Q-Ensemble

no code implementations7 Dec 2022 Chao Li

Both imitation learning (IL) and learning from demonstrations (LfD) improve the training process by using expert demonstrations, but imperfect expert demonstrations can mislead policy improvement.

Continuous Control Imitation Learning +2

Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks

no code implementations27 Nov 2022 Chao Li, Hao Xu, Kun He

To address these issues, we propose a novel method called Partial Message Meta Multigraph search (PMMM) to automatically optimize the neural architecture design on HINs.

Neural Architecture Search Node Classification

Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics

1 code implementation17 Nov 2022 Jiawei Jiang, Dayan Pan, Houxing Ren, Xiaohan Jiang, Chao Li, Jingyuan Wang

TRL aims to convert complicated raw trajectories into low-dimensional representation vectors, which can be applied to various downstream tasks, such as trajectory classification, clustering, and similarity computation.

Contrastive Learning Graph Attention +2

LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping

1 code implementation1 Nov 2022 Jinwei Zhang, Pascal Spincemaille, Hang Zhang, Thanh D. Nguyen, Chao Li, Jiahao Li, Ilhami Kovanlikaya, Mert R. Sabuncu, Yi Wang

In this paper, we present our new framework, called Learned Acquisition and Reconstruction Optimization (LARO), which aims to accelerate the multi-echo gradient echo (mGRE) pulse sequence for QSM.

Instance Segmentation for Chinese Character Stroke Extraction, Datasets and Benchmarks

1 code implementation25 Oct 2022 Lizhao Liu, Kunyang Lin, Shangxin Huang, Zhongli Li, Chao Li, Yunbo Cao, Qingyu Zhou

Moreover, there are no standardized benchmarks to provide a fair comparison between different stroke extraction methods, which, we believe, is a major impediment to the development of Chinese character stroke understanding and related tasks.

Font Generation Instance Segmentation +2

Hierarchical Multi-Interest Co-Network For Coarse-Grained Ranking

no code implementations19 Oct 2022 Xu Yuan, Chen Xu, Qiwei Chen, Tao Zhuang, Hongjie Chen, Chao Li, Junfeng Ge

This paper proposes a Hierarchical Multi-Interest Co-Network (HCN) to capture users' diverse interests in the coarse-grained ranking stage.

Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation

no code implementations18 Oct 2022 Shentong Mo, Zhun Sun, Chao Li

Particularly, in the classification down-stream tasks with linear probes, our proposed method outperforms the state-of-the-art instance-wise and prototypical contrastive learning methods on the ImageNet-100 dataset by 2. 96% and the ImageNet-1K dataset by 2. 46% under the same settings of batch size and epochs.

Contrastive Learning Self-Supervised Learning

Omni-Dimensional Dynamic Convolution

1 code implementation ICLR 2022 Chao Li, Aojun Zhou, Anbang Yao

Learning a single static convolutional kernel in each convolutional layer is the common training paradigm of modern Convolutional Neural Networks (CNNs).

MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition

no code implementations31 Aug 2022 Yunhao Wang, Huixin Sun, Xiaodi Wang, Bin Zhang, Chao Li, Ying Xin, Baochang Zhang, Errui Ding, Shumin Han

We develop a simple but effective module to explore the full potential of transformers for visual representation by learning fine-grained and coarse-grained features at a token level and dynamically fusing them.

Instance Segmentation object-detection +2

AiM: Taking Answers in Mind to Correct Chinese Cloze Tests in Educational Applications

1 code implementation COLING 2022 Yusen Zhang, Zhongli Li, Qingyu Zhou, Ziyi Liu, Chao Li, Mina Ma, Yunbo Cao, Hongzhi Liu

To automatically correct handwritten assignments, the traditional approach is to use an OCR model to recognize characters and compare them to answers.

Optical Character Recognition (OCR)

Siamese Prototypical Contrastive Learning

no code implementations18 Aug 2022 Shentong Mo, Zhun Sun, Chao Li

One of the drawbacks of CSL is that the loss term requires a large number of negative samples to provide better mutual information bound ideally.

Contrastive Learning Self-Supervised Learning

Generative Action Description Prompts for Skeleton-based Action Recognition

3 code implementations ICCV 2023 Wangmeng Xiang, Chao Li, Yuxuan Zhou, Biao Wang, Lei Zhang

More specifically, we employ a pre-trained large-scale language model as the knowledge engine to automatically generate text descriptions for body parts movements of actions, and propose a multi-modal training scheme by utilizing the text encoder to generate feature vectors for different body parts and supervise the skeleton encoder for action representation learning.

Action Recognition Language Modelling +2

Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action Recognition

1 code implementation27 Jul 2022 Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Xian-Sheng Hua, Lei Zhang

For 3D video-based tasks such as action recognition, however, directly applying spatiotemporal transformers on video data will bring heavy computation and memory burdens due to the largely increased number of patches and the quadratic complexity of self-attention computation.

Action Classification Action Recognition

Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video Snippet

1 code implementation9 Jul 2022 Shihao Zou, Yuanlu Xu, Chao Li, Lingni Ma, Li Cheng, Minh Vo

In this paper, we propose Snipper, a unified framework to perform multi-person 3D pose estimation, tracking, and motion forecasting simultaneously in a single stage.

3D Pose Estimation Motion Forecasting +1

SALO: An Efficient Spatial Accelerator Enabling Hybrid Sparse Attention Mechanisms for Long Sequences

no code implementations29 Jun 2022 Guan Shen, Jieru Zhao, Quan Chen, Jingwen Leng, Chao Li, Minyi Guo

However, the quadratic complexity of self-attention w. r. t the sequence length incurs heavy computational and memory burdens, especially for tasks with long sequences.

SP-ViT: Learning 2D Spatial Priors for Vision Transformers

1 code implementation15 Jun 2022 Yuxuan Zhou, Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Lei Zhang, Margret Keuper, Xiansheng Hua

Unlike convolutional inductive biases, which are forced to focus exclusively on hard-coded local regions, our proposed SPs are learned by the model itself and take a variety of spatial relations into account.

Image Classification

Permutation Search of Tensor Network Structures via Local Sampling

1 code implementation14 Jun 2022 Chao Li, Junhua Zeng, Zerui Tao, Qibin Zhao

Recent works put much effort into tensor network structure search (TN-SS), aiming to select suitable tensor network (TN) structures, involving the TN-ranks, formats, and so on, for the decomposition or learning tasks.

Gleo-Det: Deep Convolution Feature-Guided Detector with Local Entropy Optimization for Salient Points

no code implementations27 Apr 2022 Chao Li, Yanan You, Wenli Zhou

3) With the guidance of convolution features, we define the cost function from both positive and negative sides.

Enhancing the Robustness, Efficiency, and Diversity of Differentiable Architecture Search

no code implementations10 Apr 2022 Chao Li, Jia Ning, Han Hu, Kun He

Differentiable architecture search (DARTS) has attracted much attention due to its simplicity and significant improvement in efficiency.

Multi-modal learning for predicting the genotype of glioma

no code implementations21 Mar 2022 Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li

In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks.

Clinical Knowledge

Type-Driven Multi-Turn Corrections for Grammatical Error Correction

1 code implementation Findings (ACL) 2022 Shaopeng Lai, Qingyu Zhou, Jiali Zeng, Zhongli Li, Chao Li, Yunbo Cao, Jinsong Su

First, they simply mix additionally-constructed training instances and original ones to train models, which fails to help models be explicitly aware of the procedure of gradual corrections.

Data Augmentation Grammatical Error Correction +1

Predicting conversion of mild cognitive impairment to Alzheimer's disease

no code implementations8 Mar 2022 Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Chao Li

In this study, we develop a self-supervised contrastive learning approach to generate structural brain networks from routine anatomical MRI under the guidance of diffusion MRI.

Contrastive Learning Management

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading

no code implementations8 Mar 2022 Lipei Zhang, Yiran Wei, Ying Fu, Stephen Price, Carola-Bibiane Schönlieb, Chao Li

In this proposed scheme, we design a normalized modality contrastive loss (NMC-loss), which could promote to disentangle multi-modality complementary representation of FFPE and frozen sections from the same patient.

Contrastive Learning Disentanglement +1

Fast density peaks clustering algorithm in polar coordinate system

no code implementations Applied Intelligence 2022 Chao Li, Shifei Ding, Xiao Xu, Shuying Du & Tianhao Shi

Density peaks clustering (DPC) algorithm provides an efficient method to quickly find cluster centers with decision graphs.

Clustering

$A^{3}D$: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks

no code implementations7 Mar 2022 Jialiang Sun, Wen Yao, Tingsong Jiang, Chao Li, Xiaoqian Chen

To alleviate these problems, in this paper, we first propose a novel platform called auto adversarial attack and defense ($A^{3}D$), which can help search for robust neural network architectures and efficient adversarial attacks.

Adversarial Attack Adversarial Defense +1

Exploring Structural Sparsity in Neural Image Compression

no code implementations9 Feb 2022 Shanzhi Yin, Chao Li, Wen Tan, Youneng Bao, Yongsheng Liang, Wei Liu

Neural image compression have reached or out-performed traditional methods (such as JPEG, BPG, WebP).

Image Compression

Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma

no code implementations14 Jan 2022 Yiran Wei, Chao Li, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price

Further, the collaborative learning model achieves better performance than either the CNN or the GNN alone.

Improved (Related-key) Differential-based Neural Distinguishers for SIMON and SIMECK Block Ciphers

1 code implementation11 Jan 2022 Jinyu Lu, Guoqiang Liu, Bing Sun, Chao Li, Li Liu

In CRYPTO 2019, Gohr made a pioneering attempt and successfully applied deep learning to the differential cryptanalysis against NSA block cipher SPECK32/64, achieving higher accuracy than the pure differential distinguishers.

Cryptanalysis

Context-Aware Compilation of DNN Training Pipelines across Edge and Cloud

1 code implementation Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2021 Dixi Yao, Liyao Xiang, Zifan Wang, Jiayu Xu, Chao Li, Xinbing Wang

Experimental results show that our system not only adapts well to, but also draws on the varying contexts, delivering a practical and efficient solution to edge-cloud model training.

Ranked #2 on Recommendation Systems on MovieLens 1M (Precision metric)

Feature Compression Image Classification +5

Universal Efficient Variable-rate Neural Image Compression

no code implementations18 Nov 2021 Shanzhi Yin, Chao Li, Youneng Bao, Yongsheng Liang

Recently, Learning-based image compression has reached comparable performance with traditional image codecs(such as JPEG, BPG, WebP).

Image Compression

LibCity: An Open Library for Traffic Prediction

1 code implementation International Conference on Advances in Geographic Information Systems 2021 Jingyuan Wang, Jiawei Jiang, Wenjun Jiang, Chao Li, Wayne Xin Zhao

This paper presents LibCity, a unified, comprehensive, and extensible library for traffic prediction, which provides researchers with a credible experimental tool and a convenient development framework.

Multivariate Time Series Forecasting Spatio-Temporal Forecasting +2

Ego4D: Around the World in 3,000 Hours of Egocentric Video

7 code implementations CVPR 2022 Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei HUANG, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Ziwei Zhao, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.

De-identification Ethics

L3C-Stereo: Lossless Compression for Stereo Images

no code implementations21 Aug 2021 Zihao Huang, Zhe Sun, Feng Duan, Andrzej Cichocki, Peiying Ruan, Chao Li

To tackle this, we propose L3C-Stereo, a multi-scale lossless compression model consisting of two main modules: the warping module and the probability estimation module.

Autonomous Driving

End-to-End User Behavior Retrieval in Click-Through RatePrediction Model

1 code implementation10 Aug 2021 Qiwei Chen, Changhua Pei, Shanshan Lv, Chao Li, Junfeng Ge, Wenwu Ou

Recently, researchers have found that the performance of CTR model can be improved greatly by taking user behavior sequence into consideration, especially long-term user behavior sequence.

Click-Through Rate Prediction Recommendation Systems +1

Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean

no code implementations10 Aug 2021 Balagopal Unnikrishnan, Cuong Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy

Specifically, we describe adaptations for scenarios with 2D and 3D inputs, uni and multi-label classification, and class distribution mismatch between labeled and unlabeled portions of the training data.

Classification Image Classification +1

Integrating Large Circular Kernels into CNNs through Neural Architecture Search

1 code implementation6 Jul 2021 Kun He, Chao Li, Yixiao Yang, Gao Huang, John E. Hopcroft

We first propose a simple yet efficient implementation of the convolution using circular kernels, and empirically show the significant advantages of large circular kernels over the counterpart square kernels.

Data Augmentation Neural Architecture Search

Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy

1 code implementation5 Jul 2021 Yipeng Zhou, Xuezheng Liu, Yao Fu, Di wu, Chao Li, Shui Yu

In this work, we study a crucial question which has been vastly overlooked by existing works: what are the optimal numbers of queries and replies in FL with DP so that the final model accuracy is maximized.

Federated Learning

Self-Supervised Nonlinear Transform-Based Tensor Nuclear Norm for Multi-Dimensional Image Recovery

no code implementations29 May 2021 Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang, Yi Chang, Michael K. Ng, Chao Li

Recently, transform-based tensor nuclear norm minimization methods are considered to capture low-rank tensor structures to recover third-order tensors in multi-dimensional image processing applications.

Graph-Constrained Structure Search for Tensor Network Representation

no code implementations NeurIPS 2021 Chao Li, Junhua Zeng, Zerui Tao, Qibin Zhao

Recent works paid effort on the structure search issue for tensor network (TN) representation, of which the aim is to select the optimal network for TN contraction to fit a tensor.

Egocentric Activity Recognition and Localization on a 3D Map

no code implementations20 May 2021 Miao Liu, Lingni Ma, Kiran Somasundaram, Yin Li, Kristen Grauman, James M. Rehg, Chao Li

Given a video captured from a first person perspective and the environment context of where the video is recorded, can we recognize what the person is doing and identify where the action occurs in the 3D space?

Action Localization Action Recognition +2

Motion Artifact Reduction in Quantitative Susceptibility Mapping using Deep Neural Network

no code implementations4 May 2021 Chao Li, Hang Zhang, Jinwei Zhang, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang

An approach to reduce motion artifacts in Quantitative Susceptibility Mapping using deep learning is proposed.

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Decoder Image Inpainting +1

BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification

no code implementations10 Mar 2021 Chao Li, Yiran Wei, Xi Chen, Carola-Bibiane Schonlieb

The proposed BrainNetGAN is a generative adversarial network variant to augment the brain structural connectivity matrices for binary dementia classification tasks.

Binary Classification Classification +4

Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction

no code implementations10 Mar 2021 Jinwei Zhang, Hang Zhang, Chao Li, Pascal Spincemaille, Mert Sabuncu, Thanh D. Nguyen, Yi Wang

Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific reconstruction technique compared to conventional qualitative imaging.

Image Reconstruction

NeRD: Neural Representation of Distribution for Medical Image Segmentation

1 code implementation6 Mar 2021 Hang Zhang, Rongguang Wang, Jinwei Zhang, Chao Li, Gufeng Yang, Pascal Spincemaille, Thanh Nguyen, Yi Wang

We introduce Neural Representation of Distribution (NeRD) technique, a module for convolutional neural networks (CNNs) that can estimate the feature distribution by optimizing an underlying function mapping image coordinates to the feature distribution.

Image Segmentation Lesion Segmentation +2

On the Memory Mechanism of Tensor-Power Recurrent Models

1 code implementation2 Mar 2021 Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao

Tensor-power (TP) recurrent model is a family of non-linear dynamical systems, of which the recurrence relation consists of a p-fold (a. k. a., degree-p) tensor product.

Blockchain-based Transparency Framework for Privacy Preserving Third-party Services

1 code implementation2 Feb 2021 Runhua Xu, Chao Li, James Joshi

We also formally show the security guarantee provided by TAB, and analyze the privacy guarantee and trustworthiness it provides.

Cryptography and Security Networking and Internet Architecture

Measuring Decentralization in Bitcoin and Ethereum using Multiple Metrics and Granularities

2 code implementations26 Jan 2021 Qinwei Lin, Chao Li, Xifeng Zhao, Xianhai Chen

Decentralization has been widely acknowledged as a core virtue of blockchains.

Cryptography and Security Databases

On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times

no code implementations11 Jan 2021 Yao Fu, Yipeng Zhou, Di wu, Shui Yu, Yonggang Wen, Chao Li

Then, we theoretically derive: 1) the conditions for the DP based FedAvg to converge as the number of global iterations (GI) approaches infinity; 2) the method to set the number of local iterations (LI) to minimize the negative influence of DP noises.

Federated Learning

Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation

no code implementations4 Jan 2021 Jenn-Bing Ong, Wee-Keong Ng, Ivan Tjuawinata, Chao Li, Jielin Yang, Sai None Myne, Huaxiong Wang, Kwok-Yan Lam, C. -C. Jay Kuo

The distributed tensor representations are dispersed on multiple clouds / fogs or servers / devices with metadata privacy, this provides both distributed trust and management to seamlessly secure big data storage, communication, sharing, and computation.

Dimensionality Reduction Management +1

Adversarial Attack on Deep Cross-Modal Hamming Retrieval

no code implementations ICCV 2021 Chao Li, Shangqian Gao, Cheng Deng, Wei Liu, Heng Huang

Specifically, given a target model, we first construct its substitute model to exploit cross-modal correlations within hamming space, with which we create adversarial examples by limitedly querying from a target model.

Adversarial Attack Cross-Modal Retrieval +2

Improving BERT with Syntax-aware Local Attention

1 code implementation Findings (ACL) 2021 Zhongli Li, Qingyu Zhou, Chao Li, Ke Xu, Yunbo Cao

Pre-trained Transformer-based neural language models, such as BERT, have achieved remarkable results on varieties of NLP tasks.

Machine Translation Question Answering +3

NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets

1 code implementation18 Dec 2020 Runhua Xu, James Joshi, Chao Li

We propose a novel framework, NN-EMD, to train DNN over multiple encrypted datasets collected from multiple sources.

BIG-bench Machine Learning Privacy Preserving

Bayesian optimization assisted unsupervised learning for efficient intra-tumor partitioning in MRI and survival prediction for glioblastoma patients

no code implementations5 Dec 2020 YiFan Li, Chao Li, Stephen Price, Carola-Bibiane Schönlieb, Xi Chen

Although successful in tumor sub-region segmentation and survival prediction, radiomics based on machine learning algorithms, is challenged by its robustness, due to the vague intermediate process and track changes.

Bayesian Optimization BIG-bench Machine Learning +2

How Far Does BERT Look At: Distance-based Clustering and Analysis of BERT's Attention

no code implementations COLING 2020 Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo

Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.

Clustering

Channel Pruning via Multi-Criteria based on Weight Dependency

no code implementations6 Nov 2020 Yangchun Yan, Rongzuo Guo, Chao Li, Kang Yang, Yongjun Xu

However, these methods ignore a small part of weights in the next layer which disappears as the feature map is removed.

Image Classification

An Empirical-cum-Statistical Approach to Power-Performance Characterization of Concurrent GPU Kernels

no code implementations4 Nov 2020 Nilanjan Goswami, Amer Qouneh, Chao Li, Tao Li

Growing deployment of power and energy efficient throughput accelerators (GPU) in data centers demands enhancement of power-performance co-optimization capabilities of GPUs.

Distributed, Parallel, and Cluster Computing Hardware Architecture Graphics

How Far Does BERT Look At:Distance-based Clustering and Analysis of BERT$'$s Attention

no code implementations2 Nov 2020 Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo

Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.

Clustering

Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

1 code implementation24 Oct 2020 wei he, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan zhang, Liangpei Zhang

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting.

Denoising Image Restoration

Architectural Implications of Graph Neural Networks

no code implementations2 Sep 2020 Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo

Graph neural networks (GNN) represent an emerging line of deep learning models that operate on graph structures.

Joint Generative Learning and Super-Resolution For Real-World Camera-Screen Degradation

no code implementations1 Aug 2020 Guanghao Yin, Shou-qian Sun, Chao Li, Xin Min

Firstly, the downsampling degradation GAN(DD-GAN) is trained to model the degradation and produces more various of LR images, which is validated to be efficient for data augmentation.

Data Augmentation Image Super-Resolution

Topology-Change-Aware Volumetric Fusion for Dynamic Scene Reconstruction

no code implementations ECCV 2020 Chao Li, Xiaohu Guo

In the classic volumetric fusion-based framework, a mesh is usually extracted from the TSDF volume as the canonical surface representation to help estimating deformation field.

4D reconstruction

PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration

no code implementations23 Jun 2020 Jianrong Xu, Boyu Diao, Bifeng Cui, Kang Yang, Chao Li, Yongjun Xu

Deep learning has achieved impressive results in many areas, but the deployment of edge intelligent devices is still very slow.

Model Compression

Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration

no code implementations18 Feb 2020 Cong Guo, Yangjie Zhou, Jingwen Leng, Yuhao Zhu, Zidong Du, Quan Chen, Chao Li, Bin Yao, Minyi Guo

We propose Simultaneous Multi-mode Architecture (SMA), a novel architecture design and execution model that offers general-purpose programmability on DNN accelerators in order to accelerate end-to-end applications.

H-OWAN: Multi-distorted Image Restoration with Tensor 1x1 Convolution

no code implementations29 Jan 2020 Zihao Huang, Chao Li, Feng Duan, Qibin Zhao

It is a challenging task to restore images from their variants with combined distortions.

Image Restoration

Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization

no code implementations6 Jan 2020 Wei He, Yong Chen, Naoto Yokoya, Chao Li, Qibin Zhao

In this paper, we propose a new model, named coupled tensor ring factorization (CTRF), for HSR.

Super-Resolution

Cross-Modal Learning with Adversarial Samples

1 code implementation NeurIPS 2019 Chao Li, Shangqian Gao, Cheng Deng, De Xie, Wei Liu

Extensive experiments on two cross-modal benchmark datasets show that the adversarial examples produced by our CMLA are efficient in fooling a target deep cross-modal hashing network.

Retrieval

Single Image Reflection Removal through Cascaded Refinement

2 code implementations CVPR 2020 Chao Li, Yixiao Yang, Kun He, Stephen Lin, John E. Hopcroft

IBCLN is a cascaded network that iteratively refines the estimates of transmission and reflection layers in a manner that they can boost the prediction quality to each other, and information across steps of the cascade is transferred using an LSTM.

Community Detection Reflection Removal

TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation

no code implementations14 Oct 2019 Fan Yang, Xiao Liu, Dongliang He, Chuang Gan, Jian Wang, Chao Li, Fu Li, Shilei Wen

In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into multiple short and attractive sub-videos with each one containing an unbroken story.

Highlight Detection Video Summarization

Hierarchical hidden community detection for protein complex prediction

1 code implementation8 Oct 2019 Chao Li, Kun He, Guangshuai Liu, John E. Hopcroft

Results: We propose a method called HirHide (Hierarchical Hidden Community Detection), which can be combined with traditional community detection methods to enable them to discover hierarchical hidden communities.

Molecular Networks

Image Inpainting with Learnable Bidirectional Attention Maps

1 code implementation ICCV 2019 Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, WangMeng Zuo, Xiao Liu, Shilei Wen, Errui Ding

Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.

Decoder Image Inpainting +1

Deep Concept-wise Temporal Convolutional Networks for Action Localization

2 code implementations26 Aug 2019 Xin Li, Tianwei Lin, Xiao Liu, Chuang Gan, WangMeng Zuo, Chao Li, Xiang Long, Dongliang He, Fu Li, Shilei Wen

In this paper, we empirically find that stacking more conventional temporal convolution layers actually deteriorates action classification performance, possibly ascribing to that all channels of 1D feature map, which generally are highly abstract and can be regarded as latent concepts, are excessively recombined in temporal convolution.

Action Classification Action Localization

Gated Convolutional Networks with Hybrid Connectivity for Image Classification

1 code implementation26 Aug 2019 Chuanguang Yang, Zhulin An, Hui Zhu, Xiaolong Hu, Kun Zhang, Kaiqiang Xu, Chao Li, Yongjun Xu

We propose a simple yet effective method to reduce the redundancy of DenseNet by substantially decreasing the number of stacked modules by replacing the original bottleneck by our SMG module, which is augmented by local residual.

Adversarial Defense Classification +2

User independent Emotion Recognition with Residual Signal-Image Network

no code implementations10 Aug 2019 Guanghao Yin, Shou-qian Sun, HUI ZHANG, Dian Yu, Chao Li, Ke-jun Zhang, Ning Zou

To the best of author's knowledge, our method is the first attempt to classify large scale subject-independent emotion with 7962 pieces of EDA signals from 457 subjects.

Binary Classification Emotion Recognition

Best Practices for Learning Domain-Specific Cross-Lingual Embeddings

no code implementations WS 2019 Lena Shakurova, Beata Nyari, Chao Li, Mihai Rotaru

Cross-lingual embeddings aim to represent words in multiple languages in a shared vector space by capturing semantic similarities across languages.

Transfer Learning

Multi-Objective Pruning for CNNs Using Genetic Algorithm

no code implementations2 Jun 2019 Chuanguang Yang, Zhulin An, Chao Li, Boyu Diao, Yongjun Xu

In this work, we propose a heuristic genetic algorithm (GA) for pruning convolutional neural networks (CNNs) according to the multi-objective trade-off among error, computation and sparsity.

Collaborative Spatiotemporal Feature Learning for Video Action Recognition

1 code implementation CVPR 2019 Chao Li, Qiaoyong Zhong, Di Xie, Shiliang Pu

By sharing the convolution kernels of different views, spatial and temporal features are collaboratively learned and thus benefit from each other.

Action Classification Action Recognition In Videos +2

Guaranteed Matrix Completion Under Multiple Linear Transformations

no code implementations CVPR 2019 Chao Li, Wei He, Longhao Yuan, Zhun Sun, Qibin Zhao

Low-rank matrix completion (LRMC) is a classical model in both computer vision (CV) and machine learning, and has been successfully applied to various real applications.

Image Inpainting Low-Rank Matrix Completion

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

no code implementations7 May 2019 Chao Li, Dongliang He, Xiao Liu, Yukang Ding, Shilei Wen

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks.

Image Super-Resolution Video Super-Resolution

POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

1 code implementation6 May 2019 Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao

In particular, there exist two requirements for fashion outfit recommendation: the Compatibility of the generated fashion outfits, and the Personalization in the recommendation process.

Adversarial Defense Through Network Profiling Based Path Extraction

no code implementations CVPR 2019 Yuxian Qiu, Jingwen Leng, Cong Guo, Quan Chen, Chao Li, Minyi Guo, Yuhao Zhu

Recently, researchers have started decomposing deep neural network models according to their semantics or functions.

Adversarial Defense

Multi-Interest Network with Dynamic Routing for Recommendation at Tmall

5 code implementations17 Apr 2019 Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee

Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.