Search Results for author: Gang Yu

Found 47 papers, 27 papers with code

Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization

no code implementations26 Apr 2022 Dezhao Zhu, Jiang Guo, Gang Yu, C. Y. Zhao, Hong Wang, Shenghong Ju

Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective.

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation

4 code implementations12 Apr 2022 Wenqiang Zhang, Zilong Huang, Guozhong Luo, Tao Chen, Xinggang Wang, Wenyu Liu, Gang Yu, Chunhua Shen

Although vision transformers (ViTs) have achieved great success in computer vision, the heavy computational cost hampers their applications to dense prediction tasks such as semantic segmentation on mobile devices.

Semantic Segmentation

An Energy-concentrated Wavelet Transform for Time Frequency Analysis of Transient Signals

no code implementations22 Feb 2022 Haoran Dong, Gang Yu

Transient signals are often composed of a series of modes that have multivalued time-dependent instantaneous frequency (IF), which brings challenges to the development of signal processing technology.

Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation

1 code implementation25 Nov 2021 Rui Wang, Jian Chen, Gang Yu, Li Sun, Changqian Yu, Changxin Gao, Nong Sang

Image manipulation with StyleGAN has been an increasing concern in recent years. Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit the attributes of the generated images. However, due to the limited semantic and spatial manipulation precision in these latent spaces, the existing endeavors are defeated in fine-grained StyleGAN image manipulation, i. e., local attribute translation. To address this issue, we discover attribute-specific control units, which consist of multiple channels of feature maps and modulation styles.

Image Manipulation

Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment

no code implementations10 Oct 2021 Haichao Zhang, Youcheng Ben, Weixi Zhang, Tao Chen, Gang Yu, Bin Fu

Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manipulated landmarks and those sampled from a real person.

Face Reenactment

Sketch Me A Video

no code implementations10 Oct 2021 Haichao Zhang, Gang Yu, Tao Chen, Guozhong Luo

Video creation has been an attractive yet challenging task for artists to explore.

A multi-stage semi-supervised improved deep embedded clustering method for bearing fault diagnosis under the situation of insufficient labeled samples

no code implementations28 Sep 2021 Tongda Sun, Gang Yu

The labeled dataset can be augmented by these pseudo-labeled data and then leveraged to train a bearing fault diagnosis model.

Deep Clustering

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

no code implementations30 Aug 2021 Yike Wu, Bo Zhang, Gang Yu, Weixi Zhang, Bin Wang, Tao Chen, Jiayuan Fan

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.

Fine-Grained Image Classification Semantic correspondence +2

Identification of Pediatric Respiratory Diseases Using Fine-grained Diagnosis System

no code implementations24 Aug 2021 Gang Yu, Zhongzhi Yu, Yemin Shi, Yingshuo Wang, Xiaoqing Liu, Zheming Li, Yonggen Zhao, Fenglei Sun, Yizhou Yu, Qiang Shu

The first stage structuralizes test results by extracting relevant numerical values from clinical notes, and the disease identification stage provides a diagnosis based on text-form clinical notes and the structured data obtained from the first stage.

Shuffle Transformer with Feature Alignment for Video Face Parsing

no code implementations16 Jun 2021 Rui Zhang, Yang Han, Zilong Huang, Pei Cheng, Guozhong Luo, Gang Yu, Bin Fu

This is a short technical report introducing the solution of the Team TCParser for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021.

Face Parsing

Multi-scale super-resolution generation of low-resolution scanned pathological images

1 code implementation15 May 2021 Kai Sun, Yanhua Gao, Ting Xie, Xun Wang, Qingqing Yang, Le Chen, Kuansong Wang, Gang Yu

We design a strategy to scan slides with low resolution (5X) and a super-resolution method is proposed to restore the image details when in diagnosis.

SSIM Super-Resolution

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation

4 code implementations5 Apr 2020 Changqian Yu, Changxin Gao, Jingbo Wang, Gang Yu, Chunhua Shen, Nong Sang

We propose to treat these spatial details and categorical semantics separately to achieve high accuracy and high efficiency for realtime semantic segmentation.

Real-Time Semantic Segmentation

Context Prior for Scene Segmentation

2 code implementations CVPR 2020 Changqian Yu, Jingbo Wang, Changxin Gao, Gang Yu, Chunhua Shen, Nong Sang

Given an input image and corresponding ground truth, Affinity Loss constructs an ideal affinity map to supervise the learning of Context Prior.

Scene Segmentation Scene Understanding

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

2 code implementations CVPR 2020 Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun

When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.

Graph Matching Person Re-Identification

State-Aware Tracker for Real-Time Video Object Segmentation

1 code implementation CVPR 2020 Xi Chen, Zuoxin Li, Ye Yuan, Gang Yu, Jianxin Shen, Donglian Qi

For higher efficiency, SAT takes advantage of the inter-frame consistency and deals with each target object as a tracklet.

Frame Semantic Segmentation +2

Real-Time Semantic Segmentation via Multiply Spatial Fusion Network

no code implementations17 Nov 2019 Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu, Feng Lu

Specifically, it achieves 77. 1% Mean IOU on the Cityscapes test dataset with the speed of 41 FPS for a 1024*2048 input, and 75. 4% Mean IOU with the speed of 91 FPS on the Camvid test dataset.

Autonomous Driving Real-Time Semantic Segmentation

SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines

3 code implementations14 Nov 2019 Yinda Xu, Zeyu Wang, Zuoxin Li, Ye Yuan, Gang Yu

Following these guidelines, we design our Fully Convolutional Siamese tracker++ (SiamFC++) by introducing both classification and target state estimation branch(G1), classification score without ambiguity(G2), tracking without prior knowledge(G3), and estimation quality score(G4).

Ranked #2 on Visual Object Tracking on VOT2017/18 (using extra training data)

Classification General Classification +3

Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

2 code implementations26 Aug 2019 Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, Gang Yu

This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).

3D Object Detection Autonomous Driving

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

7 code implementations ICCV 2019 Wenhai Wang, Enze Xie, Xiaoge Song, Yuhang Zang, Wenjia Wang, Tong Lu, Gang Yu, Chunhua Shen

Recently, some methods have been proposed to tackle arbitrary-shaped text detection, but they rarely take the speed of the entire pipeline into consideration, which may fall short in practical applications. In this paper, we propose an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing.

Scene Text Detection

TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection

no code implementations CVPR 2019 Lin Song, Shiwei Zhang, Gang Yu, Hongbin Sun

In this paper, we define these ambiguous samples as "transitional states", and propose a Transition-Aware Context Network (TACNet) to distinguish transitional states.

Action Detection Frame

Shape Robust Text Detection with Progressive Scale Expansion Network

13 code implementations CVPR 2019 Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao

Due to the fact that there are large geometrical margins among the minimal scale kernels, our method is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.

Optical Character Recognition Scene Text Detection

ThunderNet: Towards Real-time Generic Object Detection

4 code implementations28 Mar 2019 Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, Jian Sun

In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.

Object Detection

An End-to-End Network for Panoptic Segmentation

no code implementations CVPR 2019 Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang

Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.

Panoptic Segmentation

Scene Text Detection with Supervised Pyramid Context Network

2 code implementations21 Nov 2018 Enze Xie, Yuhang Zang, Shuai Shao, Gang Yu, Cong Yao, Guangyao Li

We propose a supervised pyramid context network (SPCNET) to precisely locate text regions while suppressing false positives.

Instance Segmentation Scene Text Detection +1

Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN

2 code implementations CVPR 2019 Shiyi Lan, Ruichi Yu, Gang Yu, Larry S. Davis

This encourages the network to preserve the geometric structure in Euclidean space throughout the feature extraction hierarchy.

Modeling Local Geometric Structure

DetNet: Design Backbone for Object Detection

no code implementations ECCV 2018 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

(1) Recent object detectors like FPN and RetinaNet usually involve extra stages against the task of image classification to handle the objects with various scales.

Classification General Classification +4

Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation

no code implementations ECCV 2018 Ruochen Fan, Qibin Hou, Ming-Ming Cheng, Gang Yu, Ralph R. Martin, Shi-Min Hu

We also combine our method with Mask R-CNN for instance segmentation, and demonstrated for the first time the ability of weakly supervised instance segmentation using only keyword annotations.

graph partitioning Image-level Supervised Instance Segmentation +3

CrowdHuman: A Benchmark for Detecting Human in a Crowd

1 code implementation30 Apr 2018 Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, Jian Sun

There are a total of $470K$ human instances from the train and validation subsets, and $~22. 6$ persons per image, with various kinds of occlusions in the dataset.

Ranked #5 on Pedestrian Detection on Caltech (using extra training data)

Human Detection Object Detection +1

Learning a Discriminative Feature Network for Semantic Segmentation

3 code implementations CVPR 2018 Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang

Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.

Semantic Segmentation Thermal Image Segmentation

SFace: An Efficient Network for Face Detection in Large Scale Variations

no code implementations18 Apr 2018 Jianfeng Wang, Ye Yuan, Boxun Li, Gang Yu, Sun Jian

A new dataset called 4K-Face is also introduced to evaluate the performance of face detection with extreme large scale variations.

Face Detection Face Recognition

DetNet: A Backbone network for Object Detection

2 code implementations17 Apr 2018 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

Due to the gap between the image classification and object detection, we propose DetNet in this paper, which is a novel backbone network specifically designed for object detection.

Classification General Classification +4

SOT for MOT

no code implementations4 Dec 2017 Qizheng He, Jia-Nan Wu, Gang Yu, Chi Zhang

Another contribution is that we show with a deep learning based appearance model, it is easy to associate detections of the same object efficiently and also with high accuracy.

Multiple Object Tracking

Light-Head R-CNN: In Defense of Two-Stage Object Detector

5 code implementations20 Nov 2017 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

More importantly, simply replacing the backbone with a tiny network (e. g, Xception), our Light-Head R-CNN gets 30. 7 mmAP at 102 FPS on COCO, significantly outperforming the single-stage, fast detectors like YOLO and SSD on both speed and accuracy.

Cascaded Pyramid Network for Multi-Person Pose Estimation

4 code implementations CVPR 2018 Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, Jian Sun

In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.

Keypoint Detection Multi-Person Pose Estimation

MegDet: A Large Mini-Batch Object Detector

6 code implementations CVPR 2018 Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, Jian Sun

The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design.

Object Detection

Face Attention Network: An Effective Face Detector for the Occluded Faces

1 code implementation20 Nov 2017 Jianfeng Wang, Ye Yuan, Gang Yu

The performance of face detection has been largely improved with the development of convolutional neural network.

Data Augmentation Occluded Face Detection

Large Kernel Matters -- Improve Semantic Segmentation by Global Convolutional Network

2 code implementations CVPR 2017 Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, Jian Sun

One of recent trends [30, 31, 14] in network architec- ture design is stacking small filters (e. g., 1x1 or 3x3) in the entire network because the stacked small filters is more ef- ficient than a large kernel, given the same computational complexity.

Semantic Segmentation

Fast Action Proposals for Human Action Detection and Search

no code implementations CVPR 2015 Gang Yu, Junsong Yuan

Assuming each action is performed by a human with meaningful motion, both appearance and motion cues are utilized to measure the actionness of the video tubes.

Action Detection Video Segmentation +1

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