Search Results for author: Biao Wang

Found 29 papers, 10 papers with code

Optimal Proposal Learning for Deployable End-to-End Pedestrian Detection

no code implementations CVPR 2023 Xiaolin Song, Binghui Chen, Pengyu Li, Jun-Yan He, Biao Wang, Yifeng Geng, Xuansong Xie, Honggang Zhang

End-to-end pedestrian detection focuses on training a pedestrian detection model via discarding the Non-Maximum Suppression (NMS) post-processing.

Pedestrian Detection

Video Object of Interest Segmentation

no code implementations6 Dec 2022 Siyuan Zhou, Chunru Zhan, Biao Wang, Tiezheng Ge, Yuning Jiang, Li Niu

Given a video and a target image of interest, our objective is to simultaneously segment and track all objects in the video that are relevant to the target image.

Semantic Segmentation Video Object Segmentation +1

Motion Transformer for Unsupervised Image Animation

1 code implementation28 Sep 2022 Jiale Tao, Biao Wang, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan

Image animation aims to animate a source image by using motion learned from a driving video.

Image Animation

Spatio-Temporal Relation Learning for Video Anomaly Detection

no code implementations27 Sep 2022 Hui Lv, Zhen Cui, Biao Wang, Jian Yang

Anomaly identification is highly dependent on the relationship between the object and the scene, as different/same object actions in same/different scenes may lead to various degrees of normality and anomaly.

Anomaly Detection Knowledge Graph Embedding +2

Language Supervised Training for Skeleton-based Action Recognition

1 code implementation10 Aug 2022 Wangmeng Xiang, Chao Li, Yuxuan Zhou, Biao Wang, Lei Zhang

More specifically, we employ a large-scale language model as the knowledge engine to provide text descriptions for body parts movements of actions, and propose a multi-modal training scheme by utilizing the text encoder to generate feature vectors for different body parts and supervise the skeleton encoder for action representation learning.

Action Recognition Language Modelling +2

Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action Recognition

1 code implementation27 Jul 2022 Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Xian-Sheng Hua, Lei Zhang

For 3D video-based tasks such as action recognition, however, directly applying spatiotemporal transformers on video data will bring heavy computation and memory burdens due to the largely increased number of patches and the quadratic complexity of self-attention computation.

Action Classification Action Recognition

Approximate synchronization of coupled multi-valued logical networks

no code implementations14 Jul 2022 Rong Zhao, Jun-e Feng, Biao Wang

According to the initial state set from which both systems start, two kinds of approximate synchronization problem, local approximate synchronization and global approximate synchronization, are proposed for the first time.

SP-ViT: Learning 2D Spatial Priors for Vision Transformers

1 code implementation15 Jun 2022 Yuxuan Zhou, Wangmeng Xiang, Chao Li, Biao Wang, Xihan Wei, Lei Zhang, Margret Keuper, Xiansheng Hua

Unlike convolutional inductive biases, which are forced to focus exclusively on hard-coded local regions, our proposed SPs are learned by the model itself and take a variety of spatial relations into account.

Image Classification

Estimation of Reliable Proposal Quality for Temporal Action Detection

1 code implementation25 Apr 2022 Junshan Hu, Chaoxu Guo, Liansheng Zhuang, Biao Wang, Tiezheng Ge, Yuning Jiang, Houqiang Li

For the region perspective, we introduce Region Evaluate Module (REM) which uses a new and efficient sampling method for proposal feature representation containing more contextual information compared with point feature to refine category score and proposal boundary.

Action Detection

Dense Learning based Semi-Supervised Object Detection

1 code implementation CVPR 2022 Binghui Chen, Pengyu Li, Xiang Chen, Biao Wang, Lei Zhang, Xian-Sheng Hua

Semi-supervised object detection (SSOD) aims to facilitate the training and deployment of object detectors with the help of a large amount of unlabeled data.

object-detection Object Detection +1

Structure-Aware Motion Transfer with Deformable Anchor Model

1 code implementation CVPR 2022 Jiale Tao, Biao Wang, Borun Xu, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan

Specifically, inspired by the known deformable part model (DPM), our DAM introduces two types of anchors or keypoints: i) a number of motion anchors that capture both appearance and motion information from the source image and driving video; ii) a latent root anchor, which is linked to the motion anchors to facilitate better learning of the representations of the object structure information.

Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes

no code implementations8 Mar 2022 Xi Weng, Yan Yan, Genshun Dong, Chang Shu, Biao Wang, Hanzi Wang, Ji Zhang

This shows that DMA-Net provides a good tradeoff between segmentation quality and speed for semantic segmentation in street scenes.

Real-Time Semantic Segmentation

Move As You Like: Image Animation in E-Commerce Scenario

1 code implementation19 Dec 2021 Borun Xu, Biao Wang, Jiale Tao, Tiezheng Ge, Yuning Jiang, Wen Li, Lixin Duan

Creative image animations are attractive in e-commerce applications, where motion transfer is one of the import ways to generate animations from static images.

Image Animation

Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting

1 code implementation ICCV 2021 Binghui Chen, Zhaoyi Yan, Ke Li, Pengyu Li, Biao Wang, WangMeng Zuo, Lei Zhang

In crowd counting, due to the problem of laborious labelling, it is perceived intractability of collecting a new large-scale dataset which has plentiful images with large diversity in density, scene, etc.

Crowd Counting

Interactive Self-Training With Mean Teachers for Semi-Supervised Object Detection

no code implementations CVPR 2021 Qize Yang, Xihan Wei, Biao Wang, Xian-Sheng Hua, Lei Zhang

Specifically, to alleviate the instability among the detection results in different iterations, we propose using nonmaximum suppression to fuse the detection results from different iterations.

object-detection Object Detection +1

Virtual Fully-Connected Layer: Training a Large-Scale Face Recognition Dataset With Limited Computational Resources

1 code implementation CVPR 2021 Pengyu Li, Biao Wang, Lei Zhang

This is because the classification paradigm needs to train a fully connected layer as the category classifier, and its parameters will be in the hundreds of millions if the training dataset contains millions of identities.

Face Recognition Metric Learning

VirFace: Enhancing Face Recognition via Unlabeled Shallow Data

no code implementations CVPR 2021 Wenyu Li, Tianchu Guo, Pengyu Li, Binghui Chen, Biao Wang, WangMeng Zuo, Lei Zhang

In this paper, we propose a novel face recognition method, named VirFace, to effectively apply the unlabeled shallow data for face recognition.

Face Recognition

On Identification of Boolean Control Networks

no code implementations29 Apr 2021 Biao Wang, Jun-e Feng, Daizhan Cheng

A new analytical framework consisting of two phenomena: single sample and multiple samples, is proposed to deal with the identification problem of Boolean control networks (BCNs) systematically and comprehensively.

All-fiber mode-locked ytterbium-doped fiber laser with a saturable absorber based on nonlinear Kerr beam cleanup effect

no code implementations24 Jul 2020 Baofu Zhang, Shanchao Ma, Sihua Lu, Qiurun He, Jing Guo, Zhongxing Jiao, Biao Wang

We theoretically and experimentally demonstrate a novel mode-locked ytterbium-doped fiber laser with a saturable absorber based on nonlinear Kerr beam cleanup effect.


Continual Local Replacement for Few-shot Learning

no code implementations23 Jan 2020 Canyu Le, Zhonggui Chen, Xihan Wei, Biao Wang, Lei Zhang

The goal of few-shot learning is to learn a model that can recognize novel classes based on one or few training data.

Few-Shot Learning General Classification

Learning Continually from Low-shot Data Stream

no code implementations27 Aug 2019 Canyu Le, Xihan Wei, Biao Wang, Lei Zhang, Zhonggui Chen

To solve these two limits, the deep learning model should not only be able to learn from a few of data, but also incrementally learn new concepts from data stream over time without forgetting the previous knowledge.

Image Classification

AIBench: An Industry Standard Internet Service AI Benchmark Suite

no code implementations13 Aug 2019 Wanling Gao, Fei Tang, Lei Wang, Jianfeng Zhan, Chunxin Lan, Chunjie Luo, Yunyou Huang, Chen Zheng, Jiahui Dai, Zheng Cao, Daoyi Zheng, Haoning Tang, Kunlin Zhan, Biao Wang, Defei Kong, Tong Wu, Minghe Yu, Chongkang Tan, Huan Li, Xinhui Tian, Yatao Li, Junchao Shao, Zhenyu Wang, Xiaoyu Wang, Hainan Ye

On the basis of the AIBench framework, abstracting the real-world data sets and workloads from one of the top e-commerce providers, we design and implement the first end-to-end Internet service AI benchmark, which contains the primary modules in the critical paths of an industry scale application and is scalable to deploy on different cluster scales.

Benchmarking Learning-To-Rank

Cannot find the paper you are looking for? You can Submit a new open access paper.