Search Results for author: Yao-Wei Wang

Found 14 papers, 3 papers with code

Large Batch Optimization for Object Detection: Training COCO in 12 Minutes

no code implementations ECCV 2020 Tong Wang, Yousong Zhu, Chaoyang Zhao, Wei Zeng, Yao-Wei Wang, Jinqiao Wang, Ming Tang

Most of existing object detectors usually adopt a small training batch size ( ~16), which severely hinders the whole community from exploring large-scale datasets due to the extremely long training procedure.

object-detection Object Detection

An Asymmetric Modeling for Action Assessment

no code implementations ECCV 2020 Jibin Gao, Wei-Shi Zheng, Jia-Hui Pan, Chengying Gao, Yao-Wei Wang, Wei Zeng, Jian-Huang Lai

However, existing methods for action assessment are mostly limited to individual actions, especially lacking modeling of the asymmetric relations among agents (e. g., between persons and objects); and this limitation undermines their ability to assess actions containing asymmetrically interactive motion patterns, since there always exists subordination between agents in many interactive actions.

Action Assessment

Hybrid Dynamic-static Context-aware Attention Network for Action Assessment in Long Videos

2 code implementations13 Aug 2020 Ling-An Zeng, Fa-Ting Hong, Wei-Shi Zheng, Qi-Zhi Yu, Wei Zeng, Yao-Wei Wang, Jian-Huang Lai

However, most existing works focus only on video dynamic information (i. e., motion information) but ignore the specific postures that an athlete is performing in a video, which is important for action assessment in long videos.

Action Assessment Action Quality Assessment

Compositional Few-Shot Recognition with Primitive Discovery and Enhancing

no code implementations12 May 2020 Yixiong Zou, Shanghang Zhang, Ke Chen, Yonghong Tian, Yao-Wei Wang, José M. F. Moura

Inspired by such capability of humans, to imitate humans' ability of learning visual primitives and composing primitives to recognize novel classes, we propose an approach to FSL to learn a feature representation composed of important primitives, which is jointly trained with two parts, i. e. primitive discovery and primitive enhancing.

Few-Shot Image Classification Few-Shot Learning +1

Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning

no code implementations ICCV 2019 Limeng Qiao, Yemin Shi, Jia Li, Yao-Wei Wang, Tiejun Huang, Yonghong Tian

By solving the problem with its closed-form solution on the fly with the setup of transduction, our approach efficiently tailors an episodic-wise metric for each task to adapt all features from a shared task-agnostic embedding space into a more discriminative task-specific metric space.

Few-Shot Learning Metric Learning

P-ODN: Prototype based Open Deep Network for Open Set Recognition

no code implementations6 May 2019 Yu Shu, Yemin Shi, Yao-Wei Wang, Tiejun Huang, Yonghong Tian

Predictors for new categories are added to the classification layer to "open" the deep neural networks to incorporate new categories dynamically.

Open Set Learning

ODN: Opening the Deep Network for Open-set Action Recognition

no code implementations23 Jan 2019 Yu Shu, Yemin Shi, Yao-Wei Wang, Yixiong Zou, Qingsheng Yuan, Yonghong Tian

Most of the existing action recognition works hold the \textit{closed-set} assumption that all action categories are known beforehand while deep networks can be well trained for these categories.

Open Set Action Recognition Temporal Action Localization

A Network Framework for Noisy Label Aggregation in Social Media

no code implementations ACL 2017 Xueying Zhan, Yao-Wei Wang, Yanghui Rao, Haoran Xie, Qing Li, Fu Lee Wang, Tak-Lam Wong

This paper focuses on the task of noisy label aggregation in social media, where users with different social or culture backgrounds may annotate invalid or malicious tags for documents.

Cultural Vocal Bursts Intensity Prediction Image Classification +2

Learning long-term dependencies for action recognition with a biologically-inspired deep network

1 code implementation ICCV 2017 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

Despite a lot of research efforts devoted in recent years, how to efficiently learn long-term dependencies from sequences still remains a pretty challenging task.

Action Recognition Temporal Action Localization

Joint Network based Attention for Action Recognition

no code implementations16 Nov 2016 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

We also introduce an attention mechanism on the temporal domain to capture the long-term dependence meanwhile finding the salient portions.

Action Recognition Temporal Action Localization

Deep Transfer Learning for Person Re-identification

1 code implementation16 Nov 2016 Mengyue Geng, Yao-Wei Wang, Tao Xiang, Yonghong Tian

Second, a two-stepped fine-tuning strategy is developed to transfer knowledge from auxiliary datasets.

General Classification Image Classification +2

Sequential Deep Trajectory Descriptor for Action Recognition with Three-stream CNN

no code implementations10 Sep 2016 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

Nevertheless, most of the existing features or descriptors cannot capture motion information effectively, especially for long-term motion.

Action Recognition Temporal Action Localization

Unsupervised Cross-Dataset Transfer Learning for Person Re-Identification

no code implementations CVPR 2016 Peixi Peng, Tao Xiang, Yao-Wei Wang, Massimiliano Pontil, Shaogang Gong, Tiejun Huang, Yonghong Tian

Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are required for training.

Dictionary Learning Person Re-Identification +1

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