Search Results for author: BaoCai Yin

Found 44 papers, 21 papers with code

IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion

no code implementations28 Mar 2024 Jiapu Wang, Zheng Cui, Boyue Wang, Shirui Pan, Junbin Gao, BaoCai Yin, Wen Gao

However, existing Temporal Knowledge Graph Completion (TKGC) methods either model TKGs in a single space or neglect the heterogeneity of different curvature spaces, thus constraining their capacity to capture these intricate geometric structures.

Temporal Knowledge Graph Completion

Few-shot Object Localization

1 code implementation19 Mar 2024 Yunhan Ren, Bo Li, Chengyang Zhang, Yong Zhang, BaoCai Yin

This task achieves generalized object localization by leveraging a small number of labeled support samples to query the positional information of objects within corresponding images.

Model Optimization Object +2

BjTT: A Large-scale Multimodal Dataset for Traffic Prediction

2 code implementations8 Mar 2024 Chengyang Zhang, Yong Zhang, Qitan Shao, Jiangtao Feng, Bo Li, Yisheng Lv, Xinglin Piao, BaoCai Yin

The key challenge of the TTG task is how to associate text with the spatial structure of the road network and traffic data for generating traffic situations.

Traffic Prediction

Catastrophic Overfitting: A Potential Blessing in Disguise

no code implementations28 Feb 2024 Mengnan Zhao, Lihe Zhang, Yuqiu Kong, BaoCai Yin

To tackle this issue, we initially employ the feature activation differences between clean and adversarial examples to analyze the underlying causes of CO. Intriguingly, our findings reveal that CO can be attributed to the feature coverage induced by a few specific pathways.

Adversarial Robustness

Separable Multi-Concept Erasure from Diffusion Models

1 code implementation3 Feb 2024 Mengnan Zhao, Lihe Zhang, Tianhang Zheng, Yuqiu Kong, BaoCai Yin

Large-scale diffusion models, known for their impressive image generation capabilities, have raised concerns among researchers regarding social impacts, such as the imitation of copyrighted artistic styles.

Image Generation Machine Unlearning

Spectrum-guided Feature Enhancement Network for Event Person Re-Identification

no code implementations2 Feb 2024 Hongchen Tan, Yi Zhang, Xiuping Liu, BaoCai Yin, Nan Ma, Xin Li, Huchuan Lu

This network consists of two innovative components: the Multi-grain Spectrum Attention Mechanism (MSAM) and the Consecutive Patch Dropout Module (CPDM).

Person Re-Identification

Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation

1 code implementation31 Jan 2024 Maoyuan Ye, Jing Zhang, Juhua Liu, Chenyu Liu, BaoCai Yin, Cong Liu, Bo Du, DaCheng Tao

In terms of the AMG mode, Hi-SAM segments text stroke foreground masks initially, then samples foreground points for hierarchical text mask generation and achieves layout analysis in passing.

Hierarchical Text Segmentation Segmentation +1

DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations

1 code implementation28 Jan 2024 Jinlu Wang, Jipeng Guo, Yanfeng Sun, Junbin Gao, Shaofan Wang, Yachao Yang, BaoCai Yin

To obtain a more comprehensive embedding representation of nodes, a novel GNNs framework, dubbed Decoupled Graph Neural Networks (DGNN), is introduced.

Attribute Graph Embedding +3

EipFormer: Emphasizing Instance Positions in 3D Instance Segmentation

no code implementations9 Dec 2023 Mengnan Zhao, Lihe Zhang, Yuqiu Kong, BaoCai Yin

It enhances the initial instance positions through weighted farthest point sampling and further refines the instance positions and proposals using aggregation averaging and center matching.

3D Instance Segmentation Position +1

ChatTraffic: Text-to-Traffic Generation via Diffusion Model

1 code implementation27 Nov 2023 Chengyang Zhang, Yong Zhang, Qitan Shao, Bo Li, Yisheng Lv, Xinglin Piao, BaoCai Yin

The key challenge of the TTG task is how to associate text with the spatial structure of the road network and traffic data for generating traffic situations.

Traffic Prediction

Center Focusing Network for Real-Time LiDAR Panoptic Segmentation

1 code implementation CVPR 2023 Xiaoyan Li, Gang Zhang, Boyue Wang, Yongli Hu, BaoCai Yin

LiDAR panoptic segmentation facilitates an autonomous vehicle to comprehensively understand the surrounding objects and scenes and is required to run in real time.

Panoptic Segmentation Segmentation

1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking

no code implementations1 Nov 2023 Shi Yin, Shijie Huan, Shangfei Wang, Jinshui Hu, Tao Guo, Bing Yin, BaoCai Yin, Cong Liu

For temporal modeling, we propose a recurrent token mixing mechanism, an axis-landmark-positional embedding mechanism, as well as a confidence-enhanced multi-head attention mechanism to adaptively and robustly embed long-term landmark dynamics into their 1D representations; for structure modeling, we design intra-group and inter-group structure modeling mechanisms to encode the component-level as well as global-level facial structure patterns as a refinement for the 1D representations of landmarks through token communications in the spatial dimension via 1D convolutional layers.

Landmark Tracking

Distractor-aware Event-based Tracking

no code implementations22 Oct 2023 Yingkai Fu, Meng Li, Wenxi Liu, Yuanchen Wang, Jiqing Zhang, BaoCai Yin, Xiaopeng Wei, Xin Yang

We demonstrate that our tracker has superior performance against the state-of-the-art trackers in terms of both accuracy and efficiency.

Object Visual Object Tracking

Referring Image Segmentation Using Text Supervision

1 code implementation ICCV 2023 Fang Liu, Yuhao Liu, Yuqiu Kong, Ke Xu, Lihe Zhang, BaoCai Yin, Gerhard Hancke, Rynson Lau

Hence, we propose a novel weakly-supervised RIS framework to formulate the target localization problem as a classification process to differentiate between positive and negative text expressions.

Image Segmentation Object Localization +4

Fast Adversarial Training with Smooth Convergence

1 code implementation ICCV 2023 Mengnan Zhao, Lihe Zhang, Yuqiu Kong, BaoCai Yin

To address this, we analyze the training process of prior FAT work and observe that catastrophic overfitting is accompanied by the appearance of loss convergence outliers.

Adversarial Robustness

Exploring Part-Informed Visual-Language Learning for Person Re-Identification

no code implementations4 Aug 2023 Yin Lin, Cong Liu, Yehansen Chen, Jinshui Hu, Bing Yin, BaoCai Yin, Zengfu Wang

Recently, visual-language learning has shown great potential in enhancing visual-based person re-identification (ReID).

Human Parsing Person Re-Identification

A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects

1 code implementation4 Aug 2023 Jiapu Wang, Boyue Wang, Meikang Qiu, Shirui Pan, Bo Xiong, Heng Liu, Linhao Luo, Tengfei Liu, Yongli Hu, BaoCai Yin, Wen Gao

Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry.

Missing Elements Temporal Knowledge Graph Completion

Frame-Event Alignment and Fusion Network for High Frame Rate Tracking

no code implementations CVPR 2023 Jiqing Zhang, Yuanchen Wang, Wenxi Liu, Meng Li, Jinpeng Bai, BaoCai Yin, Xin Yang

The alignment module is responsible for cross-style and cross-frame-rate alignment between frame and event modalities under the guidance of the moving cues furnished by events.

Object Tracking

Single Depth-image 3D Reflection Symmetry and Shape Prediction

no code implementations ICCV 2023 Zhaoxuan Zhang, Bo Dong, Tong Li, Felix Heide, Pieter Peers, BaoCai Yin, Xin Yang

In this paper, we present Iterative Symmetry Completion Network (ISCNet), a single depth-image shape completion method that exploits reflective symmetry cues to obtain more detailed shapes.

Point Cloud Scene Completion with Joint Color and Semantic Estimation from Single RGB-D Image

no code implementations12 Oct 2022 Zhaoxuan Zhang, Xiaoguang Han, Bo Dong, Tong Li, BaoCai Yin, Xin Yang

Given a single RGB-D image, our method first predicts its semantic segmentation map and goes through the 3D volume branch to obtain a volumetric scene reconstruction as a guide to the next view inpainting step, which attempts to make up the missing information; the third step involves projecting the volume under the same view of the input, concatenating them to complete the current view RGB-D and segmentation map, and integrating all RGB-D and segmentation maps into the point cloud.

Image Inpainting Segmentation +1

NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction

no code implementations4 Jul 2022 Xueyan Yin, Feifan Li, Yanming Shen, Heng Qi, BaoCai Yin

First, a spatial-temporal graph neural network is proposed, which can capture the node-specific spatial-temporal traffic patterns of different road networks.

Traffic Prediction Transfer Learning

Soft-mask: Adaptive Substructure Extractions for Graph Neural Networks

1 code implementation11 Jun 2022 Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin

Task-relevant structures can be $localized$ or $sparse$ which are only involved in subgraphs or characterized by the interactions of subgraphs (a hierarchical perspective).

Representation Learning

DR-GAN: Distribution Regularization for Text-to-Image Generation

1 code implementation17 Apr 2022 Hongchen Tan, Xiuping Liu, BaoCai Yin, Xin Li

This paper presents a new Text-to-Image generation model, named Distribution Regularization Generative Adversarial Network (DR-GAN), to generate images from text descriptions from improved distribution learning.

Generative Adversarial Network Text-to-Image Generation

Bi-directional Object-context Prioritization Learning for Saliency Ranking

1 code implementation CVPR 2022 Xin Tian, Ke Xu, Xin Yang, Lin Du, BaoCai Yin, Rynson W. H. Lau

We observe that spatial attention works concurrently with object-based attention in the human visual recognition system.

Object Saliency Ranking

Spiking Transformers for Event-Based Single Object Tracking

no code implementations CVPR 2022 Jiqing Zhang, Bo Dong, Haiwei Zhang, Jianchuan Ding, Felix Heide, BaoCai Yin, Xin Yang

In particular, the proposed architecture features a transformer module to provide global spatial information and a spiking neural network (SNN) module for extracting temporal cues.

Object Object Tracking

A New Perspective on the Effects of Spectrum in Graph Neural Networks

1 code implementation14 Dec 2021 Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, BaoCai Yin

Many improvements on GNNs can be deemed as operations on the spectrum of the underlying graph matrix, which motivates us to directly study the characteristics of the spectrum and their effects on GNN performance.

Graph Classification Graph Property Prediction +1

Learning to Detect Instance-level Salient Objects Using Complementary Image Labels

no code implementations19 Nov 2021 Xin Tian, Ke Xu, Xin Yang, BaoCai Yin, Rynson W. H. Lau

However, it is non-trivial to use only class labels to learn instance-aware saliency information, as salient instances with high semantic affinities may not be easily separated by the labels.

Boundary Detection Object Localization +1

Temporal Knowledge Graph Reasoning Triggered by Memories

1 code implementation17 Oct 2021 Mengnan Zhao, Lihe Zhang, Yuqiu Kong, BaoCai Yin

Specifically, the transient learning network considers transient memories as a static knowledge graph, and the time-aware recurrent evolution network learns representations through a sequence of recurrent evolution units from long-short-term memories.

Attribute Decision Making +2

Object Tracking by Jointly Exploiting Frame and Event Domain

2 code implementations ICCV 2021 Jiqing Zhang, Xin Yang, Yingkai Fu, Xiaopeng Wei, BaoCai Yin, Bo Dong

Our approach's effectiveness is enforced by a novel designed cross-domain attention schemes, which can effectively enhance features based on self- and cross-domain attention schemes; The adaptiveness is guarded by a specially designed weighting scheme, which can adaptively balance the contribution of the two domains.

Object Object Tracking

Grassmannian Graph-attentional Landmark Selection for Domain Adaptation

no code implementations7 Sep 2021 Bin Sun, Shaofan Wang, Dehui Kong, Jinghua Li, BaoCai Yin

GGLS presents a landmark selection scheme using attention-induced neighbors of the graphical structure of samples and performs distribution adaptation and knowledge adaptation over Grassmann manifold.

Domain Adaptation

Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking

no code implementations10 Aug 2021 Jiqing Zhang, Kai Zhao, Bo Dong, Yingkai Fu, Yuxin Wang, Xin Yang, BaoCai Yin

Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking.

Visual Object Tracking

GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition

no code implementations25 May 2021 Bin Sun, Dehui Kong, Shaofan Wang, Jinghua Li, BaoCai Yin, Xiaonan Luo

In the sampling stage, we utilize a generative adversarial networks (GAN) trained by action features and word vectors of seen classes to synthesize the action features of unseen classes, which can balance the training sample data of seen classes and unseen classes.

Action Recognition Classification +3

Real-time Human Action Recognition Using Locally Aggregated Kinematic-Guided Skeletonlet and Supervised Hashing-by-Analysis Model

no code implementations24 May 2021 Bin Sun, Shaofan Wang, Dehui Kong, LiChun Wang, BaoCai Yin

To tackle all these problems, we propose a real-time 3D action recognition framework by integrating the locally aggregated kinematic-guided skeletonlet (LAKS) with a supervised hashing-by-analysis (SHA) model.

3D Action Recognition Denoising

Metro Passenger Flow Prediction via Dynamic Hypergraph Convolution Networks

no code implementations IEEE Transactions on Intelligent Transportation Systems 2021 Jingcheng Wang, Yong Zhang, Yun Wei, Yongli Hu, Xinglin Piao, BaoCai Yin

Metro passenger flow prediction is a strategically necessary demand in an intelligent transportation system to alleviate traffic pressure, coordinate operation schedules, and plan future constructions.

A Two-Stage Attentive Network for Single Image Super-Resolution

1 code implementation21 Apr 2021 Jiqing Zhang, Chengjiang Long, Yuxin Wang, Haiyin Piao, Haiyang Mei, Xin Yang, BaoCai Yin

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and contribute remarkable progress.

Image Reconstruction Image Super-Resolution +1

Smart Scribbles for Image Mating

no code implementations31 Mar 2021 Xin Yang, Yu Qiao, Shaozhe Chen, Shengfeng He, BaoCai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau

Image matting is an ill-posed problem that usually requires additional user input, such as trimaps or scribbles.

Image Matting

Automatic Comic Generation with Stylistic Multi-page Layouts and Emotion-driven Text Balloon Generation

no code implementations26 Jan 2021 Xin Yang, Zongliang Ma, Letian Yu, Ying Cao, BaoCai Yin, Xiaopeng Wei, Qiang Zhang, Rynson W. H. Lau

Finally, as opposed to using the same type of balloon as in previous works, we propose an emotion-aware balloon generation method to create different types of word balloons by analyzing the emotion of subtitles and audios.

CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering

1 code implementation18 Jan 2021 Guangyu Huo, Yong Zhang, Junbin Gao, Boyue Wang, Yongli Hu, BaoCai Yin

In this paper, we propose a cross-attention based deep clustering framework, named Cross-Attention Fusion based Enhanced Graph Convolutional Network (CaEGCN), which contains four main modules: the cross-attention fusion module which innovatively concatenates the Content Auto-encoder module (CAE) relating to the individual data and Graph Convolutional Auto-encoder module (GAE) relating to the relationship between the data in a layer-by-layer manner, and the self-supervised model that highlights the discriminative information for clustering tasks.

Clustering Deep Clustering

Breaking the Expressive Bottlenecks of Graph Neural Networks

1 code implementation14 Dec 2020 Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin

Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressiveness of graph neural networks (GNNs), showing that the neighborhood aggregation GNNs were at most as powerful as 1-WL test in distinguishing graph structures.

Graph Property Prediction

MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-Identification

1 code implementation10 Aug 2020 Hongchen Tan, Xiuping Liu, BaoCai Yin, Xin Li

This paper presents a novel person re-identification model, named Multi-Head Self-Attention Network (MHSA-Net), to prune unimportant information and capture key local information from person images.

Person Re-Identification

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