Search Results for author: Ze Wang

Found 55 papers, 15 papers with code

ST-MambaSync: The Complement of Mamba and Transformers for Spatial-Temporal in Traffic Flow Prediction

no code implementations24 Apr 2024 Zhiqi Shao, Xusheng Yao, Ze Wang, Junbin Gao

This paper introduces ST-MambaSync, an innovative traffic flow prediction model that combines transformer technology with the ST-Mamba block, representing a significant advancement in the field.

Computational Efficiency Management +1

Resting state fMRI-based brain information flow mapping

no code implementations23 Apr 2024 Ze Wang

Human brain is a massive information generation and processing machine.

ST-Mamba: Spatial-Temporal Selective State Space Model for Traffic Flow Prediction

no code implementations20 Apr 2024 Zhiqi Shao, Michael G. H. Bell, Ze Wang, D. Glenn Geers, Haoning Xi, Junbin Gao

Traffic flow prediction, a critical aspect of intelligent transportation systems, has been increasingly popular in the field of artificial intelligence, driven by the availability of extensive traffic data.

Computational Efficiency Management +1

Model-Agnostic Human Preference Inversion in Diffusion Models

no code implementations1 Apr 2024 Jeeyung Kim, Ze Wang, Qiang Qiu

Efficient text-to-image generation remains a challenging task due to the high computational costs associated with the multi-step sampling in diffusion models.

Text-to-Image Generation

Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed

no code implementations3 Jan 2024 Xuejian Li, Ze Wang, Bingqi Zhu, Fei He, Yongkang Wang, Xingxing Wang

The prevalent methods of segregating the ad auction and allocation into two distinct stages face two problems: 1) Ad auction does not consider externalities, such as the influence of actual display position and context on ad Click-Through Rate (CTR); 2) The ad allocation, which utilizes the auction-winning ad's payment to determine the display position dynamically, fails to maintain incentive compatibility (IC) for the advertisement.

Position

Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning

no code implementations CVPR 2024 Zichen Miao, Jiang Wang, Ze Wang, Zhengyuan Yang, Lijuan Wang, Qiang Qiu, Zicheng Liu

We also show the effectiveness of our RL fine-tuning framework on enhancing the diversity of image generation with different types of diffusion models including class-conditional models and text-conditional models e. g. StableDiffusion.

Decision Making Image Generation +3

Rethinking Event-based Human Pose Estimation with 3D Event Representations

1 code implementation8 Nov 2023 Xiaoting Yin, Hao Shi, Jiaan Chen, Ze Wang, Yaozu Ye, Huajian Ni, Kailun Yang, Kaiwei Wang

Experiments on EV-3DPW demonstrate that the robustness of our proposed 3D representation methods compared to traditional RGB images and event frame techniques under the same backbones.

Autonomous Driving Pose Estimation

FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving

1 code implementation14 Aug 2023 Zhonghua Yi, Hao Shi, Kailun Yang, Qi Jiang, Yaozu Ye, Ze Wang, Huajian Ni, Kaiwei Wang

Based on the modeling method, we present FocusFlow, a framework consisting of 1) a mix loss function combined with a classic photometric loss function and our proposed Conditional Point Control Loss (CPCL) function for diverse point-wise supervision; 2) a conditioned controlling model which substitutes the conventional feature encoder by our proposed Condition Control Encoder (CCE).

Autonomous Driving Optical Flow Estimation +1

Tightly-Coupled LiDAR-Visual SLAM Based on Geometric Features for Mobile Agents

no code implementations15 Jul 2023 Ke Cao, Ruiping Liu, Ze Wang, Kunyu Peng, Jiaming Zhang, Junwei Zheng, Zhifeng Teng, Kailun Yang, Rainer Stiefelhagen

On the other hand, the entire line segment detected by the visual subsystem overcomes the limitation of the LiDAR subsystem, which can only perform the local calculation for geometric features.

Autonomous Navigation Pose Estimation +2

Close-up View synthesis by Interpolating Optical Flow

no code implementations12 Jul 2023 Xinyi Bai, Ze Wang, Lu Yang, Hong Cheng

The virtual viewpoint is perceived as a new technique in virtual navigation, as yet not supported due to the lack of depth information and obscure camera parameters.

Optical Flow Estimation

Towards Anytime Optical Flow Estimation with Event Cameras

1 code implementation11 Jul 2023 Yaozu Ye, Hao Shi, Kailun Yang, Ze Wang, Xiaoting Yin, Yining Lin, Mao Liu, Yaonan Wang, Kaiwei Wang

We then propose EVA-Flow, an EVent-based Anytime Flow estimation network to produce high-frame-rate event optical flow with only low-frame-rate optical flow ground truth for supervision.

Autonomous Driving Motion Estimation +1

LF-PGVIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras using Points and Geodesic Segments

1 code implementation11 Jun 2023 Ze Wang, Kailun Yang, Hao Shi, Yufan Zhang, Zhijie Xu, Fei Gao, Kaiwei Wang

The purpose of our research is to unleash the potential of point-line odometry with large-FoV omnidirectional cameras, even for cameras with negative-plane FoV.

Line Detection

MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed

no code implementations17 Apr 2023 Xiaowen Shi, Ze Wang, Yuanying Cai, Xiaoxu Wu, Fan Yang, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang

There are two types of data employed to train reinforcement learning (RL) model for position allocation, named strategy data and random data.

Imitation Learning Position +2

Binary Latent Diffusion

no code implementations CVPR 2023 Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu

In this paper, we show that a binary latent space can be explored for compact yet expressive image representations.

Image Generation Quantization +1

PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce

1 code implementation6 Feb 2023 Xiaowen Shi, Fan Yang, Ze Wang, Xiaoxu Wu, Muzhi Guan, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang

Then we design a novel omnidirectional attention mechanism in OCPM to capture the context information in the permutation.

Re-Ranking

Energy-Inspired Self-Supervised Pretraining for Vision Models

no code implementations2 Feb 2023 Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu

In the proposed framework, we model energy estimation and data restoration as the forward and backward passes of a single network without any auxiliary components, e. g., an extra decoder.

Colorization Decoder +3

HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization

no code implementations15 Nov 2022 Jingang Qu, Thibault Faney, Ze Wang, Patrick Gallinari, Soleiman Yousef, Jean-Charles de Hemptinne

This paper presents a novel DG method, called HMOE: Hypernetwork-based Mixture of Experts (MoE), which does not rely on domain labels and is more interpretable.

Domain Generalization

Motion correction in MRI using deep learning and a novel hybrid loss function

1 code implementation19 Oct 2022 Lei Zhang, Xiaoke Wang, Michael Rawson, Radu Balan, Edward H. Herskovits, Elias Melhem, Linda Chang, Ze Wang, Thomas Ernst

Evaluation used simulated T1 and T2-weighted axial, coronal, and sagittal images unseen during training, as well as T1-weighted images with motion artifacts from real scans.

SSIM

LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile Agents

3 code implementations12 Sep 2022 Ze Wang, Kailun Yang, Hao Shi, Peng Li, Fei Gao, Jian Bai, Kaiwei Wang

As loop closure on wide-FoV panoramic data further comes with a large number of outliers, traditional outlier rejection methods are not directly applicable.

Autonomous Driving Simultaneous Localization and Mapping

Acceleration of cerebral blood flow and arterial transit time maps estimation from multiple post-labeling delay arterial spin-labeled MRI via deep learning

no code implementations13 Jun 2022 Yiran Li, Ze Wang

The proposed method significantly reduces the number of PLDs from 6 to 2 on ATT and even to single PLD on CBF without sacrificing the SNR.

Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning

no code implementations7 Jun 2022 Ziqi Zhou, Li Lian, Yilong Yin, Ze Wang

Guided by that maximum rate, a novel and efficient hierarchical network pruning algorithm is developed to maximally condense the neuronal network structure without sacrificing network performance.

Network Pruning Neural Network Compression

NMA: Neural Multi-slot Auctions with Externalities for Online Advertising

no code implementations20 May 2022 Guogang Liao, Xuejian Li, Ze Wang, Fan Yang, Muzhi Guan, Bingqi Zhu, Yongkang Wang, Xingxing Wang, Dong Wang

Although VCG-based multi-slot auctions (e. g., VCG, WVCG) make it theoretically possible to model global externalities (e. g., the order and positions of ads and so on), they lack an efficient balance of both revenue and social welfare.

Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation

no code implementations2 Apr 2022 Ze Wang, Guogang Liao, Xiaowen Shi, Xiaoxu Wu, Chuheng Zhang, Bingqi Zhu, Yongkang Wang, Xingxing Wang, Dong Wang

Ads allocation, which involves allocating ads and organic items to limited slots in feed with the purpose of maximizing platform revenue, has become a research hotspot.

reinforcement-learning Reinforcement Learning (RL)

Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks

no code implementations2 Apr 2022 Ze Wang, Guogang Liao, Xiaowen Shi, Xiaoxu Wu, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

With the recent prevalence of reinforcement learning (RL), there have been tremendous interests in utilizing RL for ads allocation in recommendation platforms (e. g., e-commerce and news feed sites).

Contrastive Learning Reinforcement Learning (RL)

Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocation

no code implementations1 Apr 2022 Guogang Liao, Xiaowen Shi, Ze Wang, Xiaoxu Wu, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

A mixed list of ads and organic items is usually displayed in feed and how to allocate the limited slots to maximize the overall revenue is a key problem.

Click-Through Rate Prediction reinforcement-learning +1

Image Generation using Continuous Filter Atoms

no code implementations NeurIPS 2021 Ze Wang, Seunghyun Hwang, Zichen Miao, Qiang Qiu

In this paper, we model the subspace of convolutional filters with a neural ordinary differential equation (ODE) to enable gradual changes in generated images.

Image-to-Image Translation Navigate +1

Learning to Learn Dense Gaussian Processes for Few-Shot Learning

no code implementations NeurIPS 2021 Ze Wang, Zichen Miao, XianTong Zhen, Qiang Qiu

In contrast to sparse Gaussian processes, we define a set of dense inducing variables to be of a much larger size than the support set in each task, which collects prior knowledge from experienced tasks.

Few-Shot Learning Gaussian Processes +2

Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks

no code implementations NeurIPS 2021 Zichen Miao, Ze Wang, Xiuyuan Cheng, Qiang Qiu

In this paper, we introduce spatiotemporal joint filter decomposition to decouple spatial and temporal learning, while preserving spatiotemporal dependency in a video.

Action Recognition

Continual Learning with Filter Atom Swapping

1 code implementation ICLR 2022 Zichen Miao, Ze Wang, Wei Chen, Qiang Qiu

In this paper, we first enforce a low-rank filter subspace by decomposing convolutional filters within each network layer over a small set of filter atoms.

Continual Learning

A Joint Subspace View to Convolutional Neural Networks

no code implementations29 Sep 2021 Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

In other words, a CNN is now reduced to layers of filter atoms, typically a few hundred of parameters per layer, with a common block of subspace coefficients shared across layers.

Meta-OLE: Meta-learned Orthogonal Low-Rank Embedding

no code implementations29 Sep 2021 Ze Wang, Yue Lu, Qiang Qiu

We introduce Meta-OLE, a new geometry-regularized method for fast adaptation to novel tasks in few-shot image classification.

Classification Few-Shot Image Classification +1

Cross DQN: Cross Deep Q Network for Ads Allocation in Feed

1 code implementation9 Sep 2021 Guogang Liao, Ze Wang, Xiaoxu Wu, Xiaowen Shi, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

Our model results in higher revenue and better user experience than state-of-the-art baselines in offline experiments.

Resting state fMRI-based temporal coherence mapping

no code implementations1 Sep 2021 Ze Wang

A few TCM properties were collected to measure LRTC, including the averaged correlation, anti-correlation, the ratio of correlation and anticorrelation, the mean coherent and incoherent duration, and the ratio between the coherent and incoherent time.

Cross-time functional connectivity analysis

no code implementations1 Sep 2021 Ze Wang

A large body of literature has shown the substantial inter-regional functional connectivity in the mammal brain.

Adaptive Convolutions with Per-pixel Dynamic Filter Atom

no code implementations ICCV 2021 Ze Wang, Zichen Miao, Jun Hu, Qiang Qiu

Applying feature dependent network weights have been proved to be effective in many fields.

Translation

Cirrus: A Long-range Bi-pattern LiDAR Dataset

no code implementations5 Dec 2020 Ze Wang, Sihao Ding, Ying Li, Jonas Fenn, Sohini Roychowdhury, Andreas Wallin, Lane Martin, Scott Ryvola, Guillermo Sapiro, Qiang Qiu

Point density varies significantly across such a long range, and different scanning patterns further diversify object representation in LiDAR.

3D Object Detection Autonomous Driving +2

Using Text to Teach Image Retrieval

no code implementations19 Nov 2020 Haoyu Dong, Ze Wang, Qiang Qiu, Guillermo Sapiro

Image retrieval relies heavily on the quality of the data modeling and the distance measurement in the feature space.

Image Retrieval Retrieval +2

ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution

no code implementations4 Sep 2020 Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

We then explicitly regularize CNN kernels by enforcing decomposed coefficients to be shared across sub-structures, while leaving each sub-structure only its own dictionary atoms, a few hundreds of parameters typically, which leads to dramatic model reductions.

Image Classification

A Learning-from-noise Dilated Wide Activation Network for denoising Arterial Spin Labeling (ASL) Perfusion Images

no code implementations15 May 2020 Danfeng Xie, Yiran Li, Hanlu Yang, Li Bai, Lei Zhang, Ze Wang

The results showed that the learning-from-noise strategy produced better output quality than ASLDN trained with relatively high SNR reference.

Image Denoising

Range Adaptation for 3D Object Detection in LiDAR

no code implementations26 Sep 2019 Ze Wang, Sihao Ding, Ying Li, Minming Zhao, Sohini Roychowdhury, Andreas Wallin, Guillermo Sapiro, Qiang Qiu

To the best of our knowledge, this paper is the first attempt to study cross-range LiDAR adaptation for object detection in point clouds.

3D Object Detection Autonomous Driving +2

A Dictionary Approach to Domain-Invariant Learning in Deep Networks

no code implementations NeurIPS 2020 Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

In this paper, we consider domain-invariant deep learning by explicitly modeling domain shifts with only a small amount of domain-specific parameters in a Convolutional Neural Network (CNN).

Domain Adaptation

Understanding Urban Dynamics via Context-aware Tensor Factorization with Neighboring Regularization

no code implementations25 Apr 2019 Jingyuan Wang, Junjie Wu, Ze Wang, Fei Gao, Zhang Xiong

In this paper, we propose a Neighbor-Regularized and context-aware Non-negative Tensor Factorization model (NR-cNTF) to discover interpretable urban dynamics from urban heterogeneous data.

Traffic Prediction

In Defense of Single-column Networks for Crowd Counting

no code implementations18 Aug 2018 Ze Wang, Zehao Xiao, Kai Xie, Qiang Qiu, Xian-Tong Zhen, Xian-Bin Cao

Crowd counting usually addressed by density estimation becomes an increasingly important topic in computer vision due to its widespread applications in video surveillance, urban planning, and intelligence gathering.

Crowd Counting Data Augmentation +1

LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

2 code implementations4 Jul 2018 Ze Wang, Weiqiang Ren, Qiang Qiu

Lane detection is to detect lanes on the road and provide the accurate location and shape of each lane.

Autonomous Driving Edge Classification +1

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

2 code implementations23 Jun 2018 Jingyuan Wang, Ze Wang, Jianfeng Li, Junjie Wu

In light of this, in this paper we propose a wavelet-based neural network structure called multilevel Wavelet Decomposition Network (mWDN) for building frequency-aware deep learning models for time series analysis.

General Classification Time Series +2

The Structure Transfer Machine Theory and Applications

1 code implementation1 Apr 2018 Baochang Zhang, Lian Zhuo, Ze Wang, Jungong Han, Xian-Tong Zhen

Representation learning is a fundamental but challenging problem, especially when the distribution of data is unknown.

Image Classification Object Tracking +1

Denoising Arterial Spin Labeling Cerebral Blood Flow Images Using Deep Learning

no code implementations29 Jan 2018 Danfeng Xie, Li Bai, Ze Wang

Arterial spin labeling perfusion MRI is a noninvasive technique for measuring quantitative cerebral blood flow (CBF), but the measurement is subject to a low signal-to-noise-ratio(SNR).

Denoising

MRF-ZOOM: A Fast Dictionary Searching Algorithm for Magnetic Resonance Fingerprinting

no code implementations17 Jun 2015 Ze Wang

Based on an empirical analysis of properties of the distance function of the acquired MRF signal and the pre-defined MRF dictionary entries, we proposed a parameter separable MRF DGS method, which breaks the multiplicative computation complexity into an additive one and enabling a resolution scalable multi-resolution DGS process, which was dubbed as MRF ZOOM.

Magnetic Resonance Fingerprinting

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