Search Results for author: Lei Bai

Found 77 papers, 35 papers with code

FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation

no code implementations3 Jun 2024 Kun Chen, Tao Chen, Peng Ye, Hao Chen, Kang Chen, Tao Han, Wanli Ouyang, Lei Bai

Data assimilation is a vital component in modern global medium-range weather forecasting systems to obtain the best estimation of the atmospheric state by combining the short-term forecast and observations.

Weather Forecasting

ORCA: A Global Ocean Emulator for Multi-year to Decadal Predictions

no code implementations24 May 2024 Zijie Guo, Pumeng Lyu, Fenghua Ling, Jing-Jia Luo, Niklas Boers, Wanli Ouyang, Lei Bai

Hindcasts of key oceanic variables demonstrate ORCA's remarkable prediction skills in predicting ocean variations compared with state-of-the-art numerical OGCMs and abilities in capturing occurrences of extreme events at the subsurface ocean and ENSO vertical patterns.

VAE-Var: Variational-Autoencoder-Enhanced Variational Assimilation

no code implementations22 May 2024 Yi Xiao, Qilong Jia, Wei Xue, Lei Bai

Data assimilation refers to a set of algorithms designed to compute the optimal estimate of a system's state by refining the prior prediction (known as background states) using observed data.

Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

1 code implementation22 May 2024 Wanghan Xu, Fenghua Ling, Wenlong Zhang, Tao Han, Hao Chen, Wanli Ouyang, Lei Bai

Data-driven artificial intelligence (AI) models have made significant advancements in weather forecasting, particularly in medium-range and nowcasting.

Weather Forecasting

CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer

no code implementations6 May 2024 Tao Han, Zhenghao Chen, Song Guo, Wanghan Xu, Lei Bai

To mitigate this issue, we introduce an efficient neural codec, the Variational Autoencoder Transformer (VAEformer), for extreme compression of climate data to significantly reduce data storage cost, making AI-based meteorological research portable to researchers.

Weather Forecasting

G-Refine: A General Quality Refiner for Text-to-Image Generation

1 code implementation29 Apr 2024 Chunyi Li, HaoNing Wu, Hongkun Hao, ZiCheng Zhang, Tengchaun Kou, Chaofeng Chen, Lei Bai, Xiaohong Liu, Weisi Lin, Guangtao Zhai

Based on the mechanisms of the Human Visual System (HVS) and syntax trees, the first two indicators can respectively identify the perception and alignment deficiencies, and the last module can apply targeted quality enhancement accordingly.

Text-to-Image Generation

RS-Mamba for Large Remote Sensing Image Dense Prediction

1 code implementation3 Apr 2024 Sijie Zhao, Hao Chen, Xueliang Zhang, Pengfeng Xiao, Lei Bai, Wanli Ouyang

RSM is specifically designed to capture the global context of remote sensing images with linear complexity, facilitating the effective processing of large VHR images.

Building change detection for remote sensing images Change Detection +1

A Survey on Long Video Generation: Challenges, Methods, and Prospects

no code implementations25 Mar 2024 Chengxuan Li, Di Huang, Zeyu Lu, Yang Xiao, Qingqi Pei, Lei Bai

Video generation is a rapidly advancing research area, garnering significant attention due to its broad range of applications.

Video Generation

HVDistill: Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation

1 code implementation18 Mar 2024 Sha Zhang, Jiajun Deng, Lei Bai, Houqiang Li, Wanli Ouyang, Yanyong Zhang

We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in an unsupervised man- ner.

Knowledge Distillation NER +1

CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling

no code implementations6 Feb 2024 Junchao Gong, Lei Bai, Peng Ye, Wanghan Xu, Na Liu, Jianhua Dai, Xiaokang Yang, Wanli Ouyang

Precipitation nowcasting based on radar data plays a crucial role in extreme weather prediction and has broad implications for disaster management.

Management

ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast

1 code implementation2 Feb 2024 Wanghan Xu, Kang Chen, Tao Han, Hao Chen, Wanli Ouyang, Lei Bai

Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to traditional physics-based dynamical models.

Value prediction

Improving Global Weather and Ocean Wave Forecast with Large Artificial Intelligence Models

no code implementations30 Jan 2024 Fenghua Ling, Lin Ouyang, Boufeniza Redouane Larbi, Jing-Jia Luo, Tao Han, Xiaohui Zhong, Lei Bai

The rapid advancement of artificial intelligence technologies, particularly in recent years, has led to the emergence of several large parameter artificial intelligence weather forecast models.

Computational Efficiency Weather Forecasting

Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning

1 code implementation23 Jan 2024 Zhishuai Li, Yunhao Nie, Ziyue Li, Lei Bai, Yisheng Lv, Rui Zhao

As a pre-trained paradigm, we conduct the Kriging task from a new perspective of representation: we aim to first learn robust and general representations and then recover attributes from representations.

Attribute Self-Supervised Learning

Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method

no code implementations22 Jan 2024 Zili Liu, Hao Chen, Lei Bai, Wenyuan Li, Keyan Chen, Zhengyi Wang, Wanli Ouyang, Zhengxia Zou, Zhenwei Shi

In this paper, we extend meteorological downscaling to arbitrary scattered station scales, establish a brand new benchmark and dataset, and retrieve meteorological states at any given station location from a coarse-resolution meteorological field.

Super-Resolution Weather Forecasting

Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting

1 code implementation8 Jan 2024 Pengxin Guo, Pengrong Jin, Ziyue Li, Lei Bai, Yu Zhang

To make the model trained on historical data better adapt to future data in a fully online manner, this paper conducts the first study of the online test-time adaptation techniques for spatial-temporal traffic flow forecasting problems.

Test-time Adaptation Traffic Prediction

Q-Refine: A Perceptual Quality Refiner for AI-Generated Image

1 code implementation2 Jan 2024 Chunyi Li, HaoNing Wu, ZiCheng Zhang, Hongkun Hao, Kaiwei Zhang, Lei Bai, Xiaohong Liu, Xiongkuo Min, Weisi Lin, Guangtao Zhai

With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge.

Image Quality Assessment

Towards an end-to-end artificial intelligence driven global weather forecasting system

no code implementations18 Dec 2023 Kun Chen, Lei Bai, Fenghua Ling, Peng Ye, Tao Chen, Jing-Jia Luo, Hao Chen, Yi Xiao, Kang Chen, Tao Han, Wanli Ouyang

Initial states are typically generated by traditional data assimilation components, which are computational expensive and time-consuming.

Weather Forecasting

ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks

no code implementations16 Dec 2023 Pumeng Lyu, Tao Tang, Fenghua Ling, Jing-Jia Luo, Niklas Boers, Wanli Ouyang, Lei Bai

Recent studies have shown that deep learning (DL) models can skillfully predict the El Ni\~no-Southern Oscillation (ENSO) forecasts over 1. 5 years ahead.

VisionTraj: A Noise-Robust Trajectory Recovery Framework based on Large-scale Camera Network

1 code implementation11 Dec 2023 Zhishuai Li, Ziyue Li, Xiaoru Hu, Guoqing Du, Yunhao Nie, Feng Zhu, Lei Bai, Rui Zhao

Trajectory recovery based on the snapshots from the city-wide multi-camera network facilitates urban mobility sensing and driveway optimization.

Clustering Denoising +1

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

2 code implementations4 Dec 2023 Yizhou Wang, Yixuan Wu, Shixiang Tang, Weizhen He, Xun Guo, Feng Zhu, Lei Bai, Rui Zhao, Jian Wu, Tong He, Wanli Ouyang

Human-centric perception tasks, e. g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports analysis.

3D Human Pose Estimation Action Recognition +8

A Critical Perceptual Pre-trained Model for Complex Trajectory Recovery

no code implementations5 Nov 2023 Dedong Li, Ziyue Li, Zhishuai Li, Lei Bai, Qingyuan Gong, Lijun Sun, Wolfgang Ketter, Rui Zhao

Then, we propose a Multi-view Graph and Complexity Aware Transformer (MGCAT) model to encode these semantics in trajectory pre-training from two aspects: 1) adaptively aggregate the multi-view graph features considering trajectory pattern, and 2) higher attention to critical nodes in a complex trajectory.

Trajectory Recovery

Understanding Masked Autoencoders From a Local Contrastive Perspective

no code implementations3 Oct 2023 Xiaoyu Yue, Lei Bai, Meng Wei, Jiangmiao Pang, Xihui Liu, Luping Zhou, Wanli Ouyang

Masked AutoEncoder (MAE) has revolutionized the field of self-supervised learning with its simple yet effective masking and reconstruction strategies.

Contrastive Learning Data Augmentation +2

STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning

1 code implementation ICCV 2023 Tao Han, Lei Bai, Lingbo Liu, Wanli Ouyang

Scale variation is a deep-rooted problem in object counting, which has not been effectively addressed by existing scale-aware algorithms.

feature selection Object Counting

Relation-Aware Distribution Representation Network for Person Clustering with Multiple Modalities

no code implementations1 Aug 2023 Kaijian Liu, Shixiang Tang, Ziyue Li, Zhishuai Li, Lei Bai, Feng Zhu, Rui Zhao

The distribution representation of a clue is a vector consisting of the relation between this clue and all other clues from all modalities, thus being modality agnostic and good for person clustering.

Clustering Relation

Enhancing Mapless Trajectory Prediction through Knowledge Distillation

no code implementations25 Jun 2023 Yuning Wang, Pu Zhang, Lei Bai, Jianru Xue

Scene information plays a crucial role in trajectory forecasting systems for autonomous driving by providing semantic clues and constraints on potential future paths of traffic agents.

Autonomous Driving Knowledge Distillation +1

MotionGPT: Finetuned LLMs Are General-Purpose Motion Generators

no code implementations19 Jun 2023 Yaqi Zhang, Di Huang, Bin Liu, Shixiang Tang, Yan Lu, Lu Chen, Lei Bai, Qi Chu, Nenghai Yu, Wanli Ouyang

Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans.

Instruct-ReID: A Multi-purpose Person Re-identification Task with Instructions

1 code implementation CVPR 2024 Weizhen He, Yiheng Deng, Shixiang Tang, Qihao Chen, Qingsong Xie, Yizhou Wang, Lei Bai, Feng Zhu, Rui Zhao, Wanli Ouyang, Donglian Qi, Yunfeng Yan

This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.

Person Re-Identification

Dynamic Causal Graph Convolutional Network for Traffic Prediction

1 code implementation12 Jun 2023 Junpeng Lin, Ziyue Li, Zhishuai Li, Lei Bai, Rui Zhao, Chen Zhang

In this work, we propose a novel approach for traffic prediction that embeds time-varying dynamic Bayesian network to capture the fine spatiotemporal topology of traffic data.

Traffic Prediction

Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping

1 code implementation12 Jun 2023 Luxuan Wang, Lei Bai, Ziyue Li, Rui Zhao, Fugee Tsung

We evaluated the effectiveness and flexibility of our representation learning framework on correlated time series forecasting and cold-start transferring the forecasting model to new instances with limited data.

Correlated Time Series Forecasting Representation Learning +1

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

1 code implementation NeurIPS 2023 Zhenfei Yin, Jiong Wang, JianJian Cao, Zhelun Shi, Dingning Liu, Mukai Li, Lu Sheng, Lei Bai, Xiaoshui Huang, Zhiyong Wang, Jing Shao, Wanli Ouyang

To the best of our knowledge, we present one of the very first open-source endeavors in the field, LAMM, encompassing a Language-Assisted Multi-Modal instruction tuning dataset, framework, and benchmark.

MM-DAG: Multi-task DAG Learning for Multi-modal Data -- with Application for Traffic Congestion Analysis

1 code implementation5 Jun 2023 Tian Lan, Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, Chen Zhang

This encourages the multi-task design: with each DAG as a task, the MM-DAG tries to learn the multiple DAGs jointly so that their consensus and consistency are maximized.

Stimulative Training++: Go Beyond The Performance Limits of Residual Networks

no code implementations4 May 2023 Peng Ye, Tong He, Shengji Tang, Baopu Li, Tao Chen, Lei Bai, Wanli Ouyang

In this work, we aim to re-investigate the training process of residual networks from a novel social psychology perspective of loafing, and further propose a new training scheme as well as three improved strategies for boosting residual networks beyond their performance limits.

Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation

no code implementations24 Apr 2023 Zeyu Lu, Chengyue Wu, Xinyuan Chen, Yaohui Wang, Lei Bai, Yu Qiao, Xihui Liu

To mitigate those limitations, we propose Hierarchical Diffusion Autoencoders (HDAE) that exploit the fine-grained-to-abstract and lowlevel-to-high-level feature hierarchy for the latent space of diffusion models.

Image Generation Image Manipulation +1

FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead

1 code implementation6 Apr 2023 Kang Chen, Tao Han, Junchao Gong, Lei Bai, Fenghua Ling, Jing-Jia Luo, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, Yuanzheng Ci, Bin Li, Xiaokang Yang, Wanli Ouyang

We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI).

HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining

1 code implementation CVPR 2023 Shixiang Tang, Cheng Chen, Qingsong Xie, Meilin Chen, Yizhou Wang, Yuanzheng Ci, Lei Bai, Feng Zhu, Haiyang Yang, Li Yi, Rui Zhao, Wanli Ouyang

Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting.

 Ranked #1 on Pedestrian Attribute Recognition on PA-100K (using extra training data)

Attribute Autonomous Driving +5

UniHCP: A Unified Model for Human-Centric Perceptions

1 code implementation CVPR 2023 Yuanzheng Ci, Yizhou Wang, Meilin Chen, Shixiang Tang, Lei Bai, Feng Zhu, Rui Zhao, Fengwei Yu, Donglian Qi, Wanli Ouyang

When adapted to a specific task, UniHCP achieves new SOTAs on a wide range of human-centric tasks, e. g., 69. 8 mIoU on CIHP for human parsing, 86. 18 mA on PA-100K for attribute prediction, 90. 3 mAP on Market1501 for ReID, and 85. 8 JI on CrowdHuman for pedestrian detection, performing better than specialized models tailored for each task.

2D Pose Estimation Attribute +8

Multi-Scale Control Signal-Aware Transformer for Motion Synthesis without Phase

no code implementations3 Mar 2023 Lintao Wang, Kun Hu, Lei Bai, Yu Ding, Wanli Ouyang, Zhiyong Wang

As past poses often contain useful auxiliary hints, in this paper, we propose a task-agnostic deep learning method, namely Multi-scale Control Signal-aware Transformer (MCS-T), with an attention based encoder-decoder architecture to discover the auxiliary information implicitly for synthesizing controllable motion without explicitly requiring auxiliary information such as phase.

Decoder Feature Engineering +1

Saliency Guided Contrastive Learning on Scene Images

no code implementations22 Feb 2023 Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Haiyang Yang, Lei Bai, Rui Zhao, Donglian Qi, Wanli Ouyang

Despite being feasible, recent works largely overlooked discovering the most discriminative regions for contrastive learning to object representations in scene images.

Contrastive Learning Linear evaluation +2

Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation

no code implementations8 Feb 2023 Geng Zhan, Dongang Wang, Mariano Cabezas, Lei Bai, Kain Kyle, Wanli Ouyang, Michael Barnett, Chenyu Wang

An accurate and robust quantitative measurement of brain volume change is paramount for translational research and clinical applications.

Graph-Free Learning in Graph-Structured Data: A More Efficient and Accurate Spatiotemporal Learning Perspective

no code implementations27 Jan 2023 Xu Wang, Pengfei Gu, Pengkun Wang, Binwu Wang, Zhengyang Zhou, Lei Bai, Yang Wang

In this paper, with extensive and deep-going experiments, we comprehensively analyze existing spatiotemporal graph learning models and reveal that extracting adjacency matrices with carefully design strategies, which are viewed as the key of enhancing performance on graph learning, are largely ineffective.

Graph Learning

$β$-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture Search

1 code implementation16 Jan 2023 Peng Ye, Tong He, Baopu Li, Tao Chen, Lei Bai, Wanli Ouyang

To address the robustness problem, we first benchmark different NAS methods under a wide range of proxy data, proxy channels, proxy layers and proxy epochs, since the robustness of NAS under different kinds of proxies has not been explored before.

Neural Architecture Search

Towards Frame Rate Agnostic Multi-Object Tracking

1 code implementation23 Sep 2022 Weitao Feng, Lei Bai, Yongqiang Yao, Fengwei Yu, Wanli Ouyang

In this paper, we propose a Frame Rate Agnostic MOT framework with a Periodic training Scheme (FAPS) to tackle the FraMOT problem for the first time.

Multi-Object Tracking Object

Jointly Contrastive Representation Learning on Road Network and Trajectory

1 code implementation14 Sep 2022 Zhenyu Mao, Ziyue Li, Dedong Li, Lei Bai, Rui Zhao

Unlike the existing cross-scale contrastive learning methods on graphs that only contrast a graph and its belonging nodes, the contrast between road segment and trajectory is elaborately tailored via novel positive sampling and adaptive weighting strategies.

Contrastive Learning Representation Learning +1

Action Recognition With Motion Diversification and Dynamic Selection

no code implementations TIP 2022 Peiqin Zhuang, Yu Guo, Zhipeng Yu, Luping Zhou, Lei Bai, Ding Liang, Zhiyong Wang, Yali Wang, Wanli Ouyang

To address this issue, we introduce a Motion Diversification and Selection (MoDS) module to generate diversified spatio-temporal motion features and then select the suitable motion representation dynamically for categorizing the input video.

Action Recognition Computational Efficiency

Unsupervised Knowledge Adaptation for Passenger Demand Forecasting

no code implementations8 Jun 2022 Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller

These multimodal forecasting models can improve accuracy but be less practical when different parts of multimodal datasets are owned by different institutions who cannot directly share data among them.

Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains

no code implementations10 May 2022 Haiyang Yang, Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Lei Bai, Rui Zhao, Wanli Ouyang

While recent self-supervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain.

Self-Supervised Learning

DR.VIC: Decomposition and Reasoning for Video Individual Counting

2 code implementations CVPR 2022 Tao Han, Lei Bai, Junyu Gao, Qi Wang, Wanli Ouyang

Instead of relying on the Multiple Object Tracking (MOT) techniques, we propose to solve the problem by decomposing all pedestrians into the initial pedestrians who existed in the first frame and the new pedestrians with separate identities in each following frame.

Crowd Counting Density Estimation +2

Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking

1 code implementation10 Mar 2022 BoYu Chen, Peixia Li, Lei Bai, Lei Qiao, Qiuhong Shen, Bo Li, Weihao Gan, Wei Wu, Wanli Ouyang

Exploiting a general-purpose neural architecture to replace hand-wired designs or inductive biases has recently drawn extensive interest.

Visual Object Tracking

Trajectory Forecasting from Detection with Uncertainty-Aware Motion Encoding

no code implementations3 Feb 2022 Pu Zhang, Lei Bai, Jianru Xue, Jianwu Fang, Nanning Zheng, Wanli Ouyang

Trajectories obtained from object detection and tracking are inevitably noisy, which could cause serious forecasting errors to predictors built on ground truth trajectories.

object-detection Object Detection +1

PSViT: Better Vision Transformer via Token Pooling and Attention Sharing

no code implementations7 Aug 2021 BoYu Chen, Peixia Li, Baopu Li, Chuming Li, Lei Bai, Chen Lin, Ming Sun, Junjie Yan, Wanli Ouyang

Then, a compact set of the possible combinations for different token pooling and attention sharing mechanisms are constructed.

Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation

1 code implementation2 Jul 2021 Lingbo Liu, Yuying Zhu, Guanbin Li, Ziyi Wu, Lei Bai, Liang Lin

In this work, we proposed a novel neural network module termed Heterogeneous Information Aggregation Machine (HIAM), which fully exploits heterogeneous information of historical data (e. g., incomplete OD matrices, unfinished order vectors, and DO matrices) to jointly learn the evolutionary patterns of OD and DO ridership.

Time Series Analysis

Mutual CRF-GNN for Few-Shot Learning

no code implementations CVPR 2021 Shixiang Tang, Dapeng Chen, Lei Bai, Kaijian Liu, Yixiao Ge, Wanli Ouyang

In this MCGN, the labels and features of support data are used by the CRF for inferring GNN affinities in a principled and probabilistic way.

Few-Shot Learning

Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving

no code implementations27 Nov 2020 Zhenxun Yuan, Xiao Song, Lei Bai, Wengang Zhou, Zhe Wang, Wanli Ouyang

As a special design of this transformer, the information encoded in the encoder is different from that in the decoder, i. e. the encoder encodes temporal-channel information of multiple frames while the decoder decodes the spatial-channel information for the current frame in a voxel-wise manner.

3D Object Detection Autonomous Driving +4

Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network

no code implementations12 Sep 2020 Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller

Accurate demand forecasting of different public transport modes(e. g., buses and light rails) is essential for public service operation. However, the development level of various modes often varies sig-nificantly, which makes it hard to predict the demand of the modeswith insufficient knowledge and sparse station distribution (i. e., station-sparse mode).

Multi-Task Learning

Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding

no code implementations14 Jul 2020 Zhe Liu, Xianzhi Wang, Lina Yao, Jake An, Lei Bai, Ee-Peng Lim

We design a semi-supervised model based on a hierarchical embedding network to extract high-level features of consumers and to predict the top-$N$ purchase destinations of a consumer.

Spectrum-Guided Adversarial Disparity Learning

1 code implementation14 Jul 2020 Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang

It has been a significant challenge to portray intraclass disparity precisely in the area of activity recognition, as it requires a robust representation of the correlation between subject-specific variation for each activity class.

Activity Recognition Denoising

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

3 code implementations NeurIPS 2020 Lei Bai, Lina Yao, Can Li, Xianzhi Wang, Can Wang

We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.

Graph Generation Graph Neural Network +5

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