Search Results for author: Yong Rui

Found 22 papers, 2 papers with code

Learning cross space mapping via DNN using large scale click-through logs

no code implementations26 Feb 2023 Wei Yu, Kuiyuan Yang, Yalong Bai, Hongxun Yao, Yong Rui

The image and query are mapped to a common vector space via these two parts respectively, and image-query similarity is naturally defined as an inner product of their mappings in the space.

Image Classification Image Retrieval +1

Learning From Biased Soft Labels

no code implementations16 Feb 2023 Hua Yuan, Ning Xu, Yu Shi, Xin Geng, Yong Rui

We present two more comprehensive indicators to measure the effectiveness of such soft labels.

Knowledge Distillation

Delving Globally into Texture and Structure for Image Inpainting

1 code implementation17 Sep 2022 Haipeng Liu, Yang Wang, Meng Wang, Yong Rui

Our model is orthogonal to the fashionable arts, such as Convolutional Neural Networks (CNNs), Attention and Transformer model, from the perspective of texture and structure information for image inpainting.

Image Inpainting

Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation

no code implementations8 Apr 2022 Jin Yuan, Feng Hou, Yangzhou Du, Zhongchao shi, Xin Geng, Jianping Fan, Yong Rui

Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA) is very attractive for real world applications.

Domain Adaptation Self-Supervised Learning

Graph Attention Transformer Network for Multi-Label Image Classification

no code implementations8 Mar 2022 Jin Yuan, Shikai Chen, Yao Zhang, Zhongchao shi, Xin Geng, Jianping Fan, Yong Rui

Subsequently, we design the graph attention transformer layer to transfer this adjacency matrix to adapt to the current domain.

Classification Graph Attention +2

A Survey on Food Computing

no code implementations22 Aug 2018 Weiqing Min, Shuqiang Jiang, Linhu Liu, Yong Rui, Ramesh Jain

This is the first comprehensive survey that targets the study of computing technology for the food area and also offers a collection of research studies and technologies to benefit researchers and practitioners working in different food-related fields.

Computers and Society Multimedia

AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond

no code implementations5 Dec 2017 Ling-Yu Duan, Yihang Lou, Shiqi Wang, Wen Gao, Yong Rui

To practically facilitate deep neural network models in the large-scale video analysis, there are still unprecedented challenges for the large-scale video data management.


Multi-Level Attention Networks for Visual Question Answering

no code implementations CVPR 2017 Dongfei Yu, Jianlong Fu, Tao Mei, Yong Rui

To solve the challenges, we propose a multi-level attention network for visual question answering that can simultaneously reduce the semantic gap by semantic attention and benefit fine-grained spatial inference by visual attention.

Question Answering Visual Question Answering +1

Enhancing Person Re-identification in a Self-trained Subspace

1 code implementation20 Apr 2017 Xun Yang, Meng Wang, Richang Hong, Qi Tian, Yong Rui

To address this problem, in this paper, we propose a self-trained subspace learning paradigm for person re-ID which effectively utilizes both labeled and unlabeled data to learn a discriminative subspace where person images across disjoint camera views can be easily matched.

Person Re-Identification

MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

no code implementations CVPR 2016 Jun Xu, Tao Mei, Ting Yao, Yong Rui

In this paper we present MSR-VTT (standing for "ABC-Video to Text") which is a new large-scale video benchmark for video understanding, especially the emerging task of translating video to text.

Image Captioning Video Description +1

Joint Multiview Segmentation and Localization of RGB-D Images Using Depth-Induced Silhouette Consistency

no code implementations CVPR 2016 Chi Zhang, Zhiwei Li, Rui Cai, Hongyang Chao, Yong Rui

In this paper, we propose an RGB-D camera localization approach which takes an effective geometry constraint, i. e. silhouette consistency, into consideration.

Camera Localization Image Segmentation +1

Highlight Detection With Pairwise Deep Ranking for First-Person Video Summarization

no code implementations CVPR 2016 Ting Yao, Tao Mei, Yong Rui

The emergence of wearable devices such as portable cameras and smart glasses makes it possible to record life logging first-person videos.

Highlight Detection Video Summarization

Network Morphism

no code implementations5 Mar 2016 Tao Wei, Changhu Wang, Yong Rui, Chang Wen Chen

The second requirement for this network morphism is its ability to deal with non-linearity in a network.

Relaxing From Vocabulary: Robust Weakly-Supervised Deep Learning for Vocabulary-Free Image Tagging

no code implementations ICCV 2015 Jianlong Fu, Yue Wu, Tao Mei, Jinqiao Wang, Hanqing Lu, Yong Rui

The development of deep learning has empowered machines with comparable capability of recognizing limited image categories to human beings.

Query Adaptive Similarity Measure for RGB-D Object Recognition

no code implementations ICCV 2015 Yanhua Cheng, Rui Cai, Chi Zhang, Zhiwei Li, Xin Zhao, Kaiqi Huang, Yong Rui

The reasons are in two-fold: (1) existing similarity measures are sensitive to object pose and scale changes, as well as intra-class variations; and (2) effectively fusing RGB and depth cues is still an open problem.

Object Recognition

Jointly Modeling Embedding and Translation to Bridge Video and Language

no code implementations CVPR 2016 Yingwei Pan, Tao Mei, Ting Yao, Houqiang Li, Yong Rui

Our proposed LSTM-E consists of three components: a 2-D and/or 3-D deep convolutional neural networks for learning powerful video representation, a deep RNN for generating sentences, and a joint embedding model for exploring the relationships between visual content and sentence semantics.


Visualizing and Comparing Convolutional Neural Networks

no code implementations20 Dec 2014 Wei Yu, Kuiyuan Yang, Yalong Bai, Hongxun Yao, Yong Rui

Convolutional Neural Networks (CNNs) have achieved comparable error rates to well-trained human on ILSVRC2014 image classification task.

Classification General Classification +1

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