Search Results for author: Yidong Li

Found 21 papers, 4 papers with code

Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation

no code implementations1 Mar 2022 Tianjiao Jiang, Yi Jin, Tengfei Liang, Xu Wang, Yidong Li

Image semantic segmentation aims at the pixel-level classification of images, which has requirements for both accuracy and speed in practical application.

Real-Time Semantic Segmentation Scene Parsing

LighTN: Light-weight Transformer Network for Performance-overhead Tradeoff in Point Cloud Downsampling

no code implementations13 Feb 2022 Xu Wang, Yi Jin, Yigang Cen, Tao Wang, Bowen Tang, Yidong Li

Compared with traditional task-irrelevant downsampling methods, task-oriented neural networks have shown improved performance in point cloud downsampling range.

GLAN: A Graph-based Linear Assignment Network

no code implementations5 Jan 2022 He Liu, Tao Wang, Congyan Lang, Songhe Feng, Yi Jin, Yidong Li

The experimental results on a synthetic dataset reveal that our method outperforms state-of-the-art baselines and achieves consistently high accuracy with the increment of the problem size.

Multi-Object Tracking

Deep Probabilistic Graph Matching

no code implementations5 Jan 2022 He Liu, Tao Wang, Yidong Li, Congyan Lang, Songhe Feng, Haibin Ling

Most previous learning-based graph matching algorithms solve the \textit{quadratic assignment problem} (QAP) by dropping one or more of the matching constraints and adopting a relaxed assignment solver to obtain sub-optimal correspondences.

Graph Matching

Clicking Matters:Towards Interactive Human Parsing

no code implementations11 Nov 2021 Yutong Gao, Liqian Liang, Congyan Lang, Songhe Feng, Yidong Li, Yunchao Wei

In this work, we focus on Interactive Human Parsing (IHP), which aims to segment a human image into multiple human body parts with guidance from users' interactions.

Human Parsing Semantic Segmentation

MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification

no code implementations21 Oct 2021 Yajun Gao, Tengfei Liang, Yi Jin, Xiaoyan Gu, Wu Liu, Yidong Li, Congyan Lang

The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality.

Cross-Modality Person Re-identification Person Re-Identification

CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification

no code implementations18 Oct 2021 Tengfei Liang, Yi Jin, Yajun Gao, Wu Liu, Songhe Feng, Tao Wang, Yidong Li

The existing convolutional neural network-based methods mainly face the problem of insufficient perception of modalities' information, and can not learn good discriminative modality-invariant embeddings for identities, which limits their performance.

Cross-Modality Person Re-identification Person Re-Identification

Joint Graph Learning and Matching for Semantic Feature Correspondence

2 code implementations1 Sep 2021 He Liu, Tao Wang, Yidong Li, Congyan Lang, Yi Jin, Haibin Ling

In this paper, we propose a joint \emph{graph learning and matching} network, named GLAM, to explore reliable graph structures for boosting graph matching.

Graph Learning Graph Matching

A Universal Model for Cross Modality Mapping by Relational Reasoning

no code implementations26 Feb 2021 Zun Li, Congyan Lang, Liqian Liang, Tao Wang, Songhe Feng, Jun Wu, Yidong Li

With the aim of matching a pair of instances from two different modalities, cross modality mapping has attracted growing attention in the computer vision community.

Image Classification Relational Reasoning

Attention Models for Point Clouds in Deep Learning: A Survey

no code implementations22 Feb 2021 Xu Wang, Yi Jin, Yigang Cen, Tao Wang, Yidong Li

Recently, the advancement of 3D point clouds in deep learning has attracted intensive research in different application domains such as computer vision and robotic tasks.

3D Pose Estimation 3D Semantic Segmentation

Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline

no code implementations24 Jan 2021 Hu Wang, Hao Chen, Qi Wu, Congbo Ma, Yidong Li, Chunhua Shen

To address these issues, in this work we carefully design our settings and propose a new dataset including both synthetic and real traffic data in more complex scenarios.

FASG: Feature Aggregation Self-training GCN for Semi-supervised Node Classification

no code implementations1 Jan 2021 Gongpei Zhao, Tao Wang, Yidong Li, Yi Jin

Recently, Graph Convolutioal Networks (GCNs) have achieved significant success in many graph-based learning tasks, especially for node classification, due to its excellent ability in representation learning.

Classification General Classification +2

Robust Data Hiding Using Inverse Gradient Attention

no code implementations21 Nov 2020 Honglei Zhang, Hu Wang, Yuanzhouhan Cao, Chunhua Shen, Yidong Li

The neglect of considering the sensitivity of each pixel will inevitably affect the model robustness for information hiding.

Cross-layer Feature Pyramid Network for Salient Object Detection

no code implementations25 Feb 2020 Zun Li, Congyan Lang, Junhao Liew, Qibin Hou, Yidong Li, Jiashi Feng

Feature pyramid network (FPN) based models, which fuse the semantics and salient details in a progressive manner, have been proven highly effective in salient object detection.

RGB Salient Object Detection Salient Object Detection

HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization

no code implementations3 Jun 2019 Gengyu Lyu, Songhe Feng, Yi Jin, Guojun Dai, Congyan Lang, Yidong Li

Partial Label Learning (PLL) aims to learn from the data where each training instance is associated with a set of candidate labels, among which only one is correct.

Partial Label Learning

GM-PLL: Graph Matching based Partial Label Learning

no code implementations10 Jan 2019 Gengyu Lyu, Songhe Feng, Tao Wang, Congyan Lang, Yidong Li

Partial Label Learning (PLL) aims to learn from the data where each training example is associated with a set of candidate labels, among which only one is correct.

Graph Matching Partial Label Learning

Multiple-Human Parsing in the Wild

2 code implementations19 May 2017 Jianshu Li, Jian Zhao, Yunchao Wei, Congyan Lang, Yidong Li, Terence Sim, Shuicheng Yan, Jiashi Feng

To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.

Multi-Human Parsing

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