Search Results for author: Chunfeng Yuan

Found 32 papers, 9 papers with code

PromptIQA: Boosting the Performance and Generalization for No-Reference Image Quality Assessment via Prompts

no code implementations8 Mar 2024 Zewen Chen, Haina Qin, Juan Wang, Chunfeng Yuan, Bing Li, Weiming Hu, Liang Wang

On the other hand, PromptIQA is trained on a mixed dataset with two proposed data augmentation strategies to learn diverse requirements, thus enabling it to effectively adapt to new requirements.

Data Augmentation No-Reference Image Quality Assessment

Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training

no code implementations1 Mar 2024 Haowei Liu, Yaya Shi, Haiyang Xu, Chunfeng Yuan, Qinghao Ye, Chenliang Li, Ming Yan, Ji Zhang, Fei Huang, Bing Li, Weiming Hu

In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment.

Representation Learning

Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval

no code implementations26 Feb 2024 Haowei Liu, Yaya Shi, Haiyang Xu, Chunfeng Yuan, Qinghao Ye, Chenliang Li, Ming Yan, Ji Zhang, Fei Huang, Bing Li, Weiming Hu

In this work, we propose the UNIFY framework, which learns lexicon representations to capture fine-grained semantics and combines the strengths of latent and lexicon representations for video-text retrieval.

Retrieval Text Retrieval +1

GMC-IQA: Exploiting Global-correlation and Mean-opinion Consistency for No-reference Image Quality Assessment

no code implementations19 Jan 2024 Zewen Chen, Juan Wang, Bing Li, Chunfeng Yuan, Weiming Hu, Junxian Liu, Peng Li, Yan Wang, Youqun Zhang, Congxuan Zhang

Due to the subjective nature of image quality assessment (IQA), assessing which image has better quality among a sequence of images is more reliable than assigning an absolute mean opinion score for an image.

No-Reference Image Quality Assessment

Set Prediction Guided by Semantic Concepts for Diverse Video Captioning

no code implementations25 Dec 2023 Yifan Lu, Ziqi Zhang, Chunfeng Yuan, Peng Li, Yan Wang, Bing Li, Weiming Hu

Each caption in the set is attached to a concept combination indicating the primary semantic content of the caption and facilitating element alignment in set prediction.

Video Captioning

Simple and Efficient Partial Graph Adversarial Attack: A New Perspective

1 code implementation15 Aug 2023 Guanghui Zhu, Mengyu Chen, Chunfeng Yuan, Yihua Huang

To this end, we propose a totally new method named partial graph attack (PGA), which selects the vulnerable nodes as attack targets.

Adversarial Attack

HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks

no code implementations4 Jul 2023 Guanghui Zhu, Zhennan Zhu, Hongyang Chen, Chunfeng Yuan, Yihua Huang

Then, we propose a novel framework to utilize the rich type semantic information in heterogeneous graphs comprehensively, namely HAGNN (Hybrid Aggregation for Heterogeneous GNNs).

Link Prediction Node Classification +1

AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network

1 code implementation8 Jan 2023 Guanghui Zhu, Zhennan Zhu, Wenjie Wang, Zhuoer Xu, Chunfeng Yuan, Yihua Huang

Moreover, to improve the performance of the downstream graph learning task, attribute completion and the training of the heterogeneous GNN should be jointly optimized rather than viewed as two separate processes.

Attribute Graph Learning +1

ViLEM: Visual-Language Error Modeling for Image-Text Retrieval

no code implementations CVPR 2023 Yuxin Chen, Zongyang Ma, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Weiming Hu, XiaoHu Qie, Jianping Wu

ViLEM then enforces the model to discriminate the correctness of each word in the plausible negative texts and further correct the wrong words via resorting to image information.

Contrastive Learning Retrieval +3

Knowledge-enhanced Black-box Attacks for Recommendations

no code implementations21 Jul 2022 Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, Yihua Huang

Recent studies have shown that deep neural networks-based recommender systems are vulnerable to adversarial attacks, where attackers can inject carefully crafted fake user profiles (i. e., a set of items that fake users have interacted with) into a target recommender system to achieve malicious purposes, such as promote or demote a set of target items.

Attribute Recommendation Systems

Improving Visual Grounding with Visual-Linguistic Verification and Iterative Reasoning

1 code implementation CVPR 2022 Li Yang, Yan Xu, Chunfeng Yuan, Wei Liu, Bing Li, Weiming Hu

They base the visual grounding on the features from pre-generated proposals or anchors, and fuse these features with the text embeddings to locate the target mentioned by the text.

Attribute object-detection +2

CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation

no code implementations31 Mar 2022 Ziqi Zhang, Yuxin Chen, Zongyang Ma, Zhongang Qi, Chunfeng Yuan, Bing Li, Ying Shan, Weiming Hu

In this paper, we propose to CREATE, the first large-scale Chinese shoRt vidEo retrievAl and Title gEneration benchmark, to facilitate research and application in video titling and video retrieval in Chinese.

Retrieval Video Captioning +1

Transition Relation Aware Self-Attention for Session-based Recommendation

no code implementations12 Mar 2022 Guanghui Zhu, Haojun Hou, Jingfan Chen, Chunfeng Yuan, Yihua Huang

Specifically, TRASA first converts the session to a graph and then encodes the shortest path between items through the gated recurrent unit as their transition relation.

Relation Session-Based Recommendations

PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling

1 code implementation28 Apr 2021 Li Yang, Yan Xu, Shaoru Wang, Chunfeng Yuan, Ziqi Zhang, Bing Li, Weiming Hu

However, the most suitable positions for inferring different targets, i. e., the object category and boundaries, are generally different.

Object object-detection +1

Open-book Video Captioning with Retrieve-Copy-Generate Network

no code implementations CVPR 2021 Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Ying Deng, Weiming Hu

Due to the rapid emergence of short videos and the requirement for content understanding and creation, the video captioning task has received increasing attention in recent years.

Retrieval Video Captioning

DIFER: Differentiable Automated Feature Engineering

1 code implementation17 Oct 2020 Guanghui Zhu, Zhuoer Xu, Xu Guo, Chunfeng Yuan, Yihua Huang

Extensive experiments on classification and regression datasets demonstrate that DIFER can significantly improve the performance of various machine learning algorithms and outperform current state-of-the-art AutoFE methods in terms of both efficiency and performance.

Automated Feature Engineering BIG-bench Machine Learning +1

Object Relational Graph with Teacher-Recommended Learning for Video Captioning

no code implementations CVPR 2020 Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, Peijin Wang, Weiming Hu, Zheng-Jun Zha

In this paper, we propose a complete video captioning system including both a novel model and an effective training strategy.

Ranked #8 on Video Captioning on VATEX (using extra training data)

Language Modelling Video Captioning

Multimodal Semantic Attention Network for Video Captioning

no code implementations8 May 2019 Liang Sun, Bing Li, Chunfeng Yuan, Zheng-Jun Zha, Weiming Hu

Inspired by the fact that different modalities in videos carry complementary information, we propose a Multimodal Semantic Attention Network(MSAN), which is a new encoder-decoder framework incorporating multimodal semantic attributes for video captioning.

Attribute General Classification +2

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

no code implementations ECCV 2018 Yang Du, Chunfeng Yuan, Bing Li, Lili Zhao, Yangxi Li, Weiming Hu

Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps.

Action Classification Classification +1

Spatio-Temporal Self-Organizing Map Deep Network for Dynamic Object Detection From Videos

no code implementations CVPR 2017 Yang Du, Chunfeng Yuan, Bing Li, Weiming Hu, Stephen Maybank

In dynamic object detection, it is challenging to construct an effective model to sufficiently characterize the spatial-temporal properties of the background.

object-detection Object Detection

Multi-target Tracking with Motion Context in Tensor Power Iteration

no code implementations CVPR 2014 Xinchu Shi, Haibin Ling, Weiming Hu, Chunfeng Yuan, Junliang Xing

In this paper, we model interactions between neighbor targets by pair-wise motion context, and further encode such context into the global association optimization.

Multi-task Sparse Learning with Beta Process Prior for Action Recognition

no code implementations CVPR 2013 Chunfeng Yuan, Weiming Hu, Guodong Tian, Shuang Yang, Haoran Wang

In this paper, we formulate human action recognition as a novel Multi-Task Sparse Learning(MTSL) framework which aims to construct a test sample with multiple features from as few bases as possible.

Action Recognition Sparse Learning +1

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