Search Results for author: Wenhao Wu

Found 20 papers, 8 papers with code

Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video

no code implementations9 Aug 2021 Jie Wu, Wei zhang, Guanbin Li, Wenhao Wu, Xiao Tan, YingYing Li, Errui Ding, Liang Lin

In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video.

Anomaly Detection

Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network

no code implementations27 Jul 2021 Zhikang Zou, Xiaoye Qu, Pan Zhou, Shuangjie Xu, Xiaoqing Ye, Wenhao Wu, Jin Ye

In specific, at the coarse-grained stage, we design a dual-discriminator strategy to adapt source domain to be close to the targets from the perspectives of both global and local feature space via adversarial learning.

Crowd Counting Transfer Learning

Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings

2 code implementations15 Jun 2021 Hengyuan Zhao, Wenhao Wu, Yihao Liu, Dongliang He

In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed.

Colorization Semantic correspondence

Temporal Action Proposal Generation with Transformers

no code implementations25 May 2021 Lining Wang, Haosen Yang, Wenhao Wu, Hongxun Yao, Hujie Huang

Conventionally, the temporal action proposal generation (TAPG) task is divided into two main sub-tasks: boundary prediction and proposal confidence prediction, which rely on the frame-level dependencies and proposal-level relationships separately.

Temporal Action Proposal Generation

BASS: Boosting Abstractive Summarization with Unified Semantic Graph

no code implementations ACL 2021 Wenhao Wu, Wei Li, Xinyan Xiao, Jiachen Liu, Ziqiang Cao, Sujian Li, Hua Wu, Haifeng Wang

Abstractive summarization for long-document or multi-document remains challenging for the Seq2Seq architecture, as Seq2Seq is not good at analyzing long-distance relations in text.

Abstractive Text Summarization Document Summarization +1

Good Practices and A Strong Baseline for Traffic Anomaly Detection

no code implementations9 May 2021 Yuxiang Zhao, Wenhao Wu, Yue He, YingYing Li, Xiao Tan, Shifeng Chen

In this paper, we propose a straightforward and efficient framework that includes pre-processing, a dynamic track module, and post-processing.

Anomaly Detection Video Stabilization

A Comprehensive Attempt to Research Statement Generation

no code implementations25 Apr 2021 Wenhao Wu, Sujian Li

For a researcher, writing a good research statement is crucial but costs a lot of time and effort.

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

2 code implementations13 Dec 2020 Wenhao Wu, Dongliang He, Tianwei Lin, Fu Li, Chuang Gan, Errui Ding

Existing state-of-the-art methods have achieved excellent accuracy regardless of the complexity meanwhile efficient spatiotemporal modeling solutions are slightly inferior in performance.

Action Classification Action Recognition +1

Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition

1 code implementation ECCV 2020 Jin Ye, Junjun He, Xiaojiang Peng, Wenhao Wu, Yu Qiao

To this end, we propose an Attention-Driven Dynamic Graph Convolutional Network (ADD-GCN) to dynamically generate a specific graph for each image.

Composing Elementary Discourse Units in Abstractive Summarization

no code implementations ACL 2020 Zhenwen Li, Wenhao Wu, Sujian Li

In this paper, we argue that elementary discourse unit (EDU) is a more appropriate textual unit of content selection than the sentence unit in abstractive summarization.

Abstractive Text Summarization

Dynamic Inference: A New Approach Toward Efficient Video Action Recognition

no code implementations9 Feb 2020 Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Yi Yang, Shilei Wen

In a nutshell, we treat input frames and network depth of the computational graph as a 2-dimensional grid, and several checkpoints are placed on this grid in advance with a prediction module.

Action Recognition Action Recognition In Videos +1

Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes

1 code implementation ECCV 2018 Minghui Liao, Pengyuan Lyu, Minghang He, Cong Yao, Wenhao Wu, Xiang Bai

Moreover, we further investigate the recognition module of our method separately, which significantly outperforms state-of-the-art methods on both regular and irregular text datasets for scene text recognition.

Scene Text Scene Text Recognition +2

TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes

3 code implementations ECCV 2018 Shangbang Long, Jiaqiang Ruan, Wenjie Zhang, Xin He, Wenhao Wu, Cong Yao

Driven by deep neural networks and large scale datasets, scene text detection methods have progressed substantially over the past years, continuously refreshing the performance records on various standard benchmarks.

Scene Text Scene Text Detection

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