no code implementations • 17 Mar 2024 • Fuqiang Niu, Min Yang, Ang Li, Baoquan Zhang, Xiaojiang Peng, BoWen Zhang
Previous stance detection studies typically concentrate on evaluating stances within individual instances, thereby exhibiting limitations in effectively modeling multi-party discussions concerning the same specific topic, as naturally transpire in authentic social media interactions.
no code implementations • 22 Feb 2024 • Yifan Duan, Guibin Zhang, Shilong Wang, Xiaojiang Peng, Wang Ziqi, Junyuan Mao, Hao Wu, Xinke Jiang, Kun Wang
Credit card fraud poses a significant threat to the economy.
no code implementations • 14 Jan 2024 • Fan Zhang, Shuyi Mao, Qing Li, Xiaojiang Peng
Comparative evaluations with popular point-based methods on HPoint103 and the public dataset DHP19 demonstrate the dramatic outperformance of our D-CPT.
no code implementations • 14 Jan 2024 • Fan Zhang, Xiaobao Guo, Xiaojiang Peng, Alex Kot
In addition, when compared with the domain disparity existing between face datasets and FER datasets, the divergence between general datasets and FER datasets is more pronounced.
no code implementations • 19 Aug 2023 • Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang, Yang Wang
Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer vision realm.
1 code implementation • 12 Apr 2023 • Xinpeng Li, Xiaojiang Peng
Inspired by the growth of lane detection, we propose a rail database and a row-based rail detection method.
1 code implementation • 6 Dec 2022 • Lihua Fu, Haoyue Tian, Xiangping Bryce Zhai, Pan Gao, Xiaojiang Peng
Semantic segmentation usually benefits from global contexts, fine localisation information, multi-scale features, etc.
Ranked #373 on Image Classification on ImageNet
no code implementations • 12 Nov 2022 • Shuyi Mao, Xinpeng Li, Qingyang Wu, Xiaojiang Peng
Studies have proven that domain bias and label bias exist in different Facial Expression Recognition (FER) datasets, making it hard to improve the performance of a specific dataset by adding other datasets.
1 code implementation • 20 Jul 2022 • Shuyi Mao, Xinpeng Li, Junyao Chen, Xiaojiang Peng
In Learing from Synthetic Data(LSD) task, facial expression recognition (FER) methods aim to learn the representation of expression from the artificially generated data and generalise to real data.
no code implementations • 8 Jul 2022 • Xiaojiang Peng, Xiaomao Fan, Qingyang Wu, Jieyan Zhao, Pan Gao
Moreover, we present a new Coarse-to-fine Deep Smoky vehicle detection (CoDeS) framework for efficient smoky vehicle detection.
1 code implementation • 25 Apr 2022 • Haoyue Tian, Pan Gao, Xiaojiang Peng
In order to solve this problem, we revisit the deformable convolution for video interpolation, which can break the fixed grid restrictions on the kernel region, making the distribution of reference points more suitable for the shape of the object, and thus warp a more accurate interpolation frame.
no code implementations • 28 Jan 2022 • Wei Xue, Xiaojiang Peng
Stereo matching is crucial for binocular stereo vision.
no code implementations • 10 Dec 2021 • Qing Li, Xiaojiang Peng, Chuan Yan, Pan Gao, Qi Hao
In SEN, a student network is kept in a collaborative manner with supervised learning and self-supervised learning, and a teacher network conducts temporal consistency to learn useful representations and ensure the quality of point clouds reconstruction.
1 code implementation • 12 Jul 2021 • Shuyi Mao, Xinqi Fan, Xiaojiang Peng
The paper describes our proposed methodology for the seven basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2021.
1 code implementation • CVPR 2022 • Kai Wang, Shuo Wang, Panpan Zhang, Zhipeng Zhou, Zheng Zhu, Xiaobo Wang, Xiaojiang Peng, Baigui Sun, Hao Li, Yang You
This method adopts Dynamic Class Pool (DCP) for storing and updating the identities features dynamically, which could be regarded as a substitute for the FC layer.
Ranked #1 on Face Verification on IJB-C (training dataset metric)
2 code implementations • CVPR 2021 • Zhi Hou, Baosheng Yu, Yu Qiao, Xiaojiang Peng, DaCheng Tao
The proposed method can thus be used to 1) improve the performance of HOI detection, especially for the HOIs with unseen objects; and 2) infer the affordances of novel objects.
Ranked #2 on Affordance Recognition on HICO-DET(Unknown Concepts)
1 code implementation • CVPR 2021 • Zhi Hou, Baosheng Yu, Yu Qiao, Xiaojiang Peng, DaCheng Tao
With the proposed object fabricator, we are able to generate large-scale HOI samples for rare and unseen categories to alleviate the open long-tailed issues in HOI detection.
Ranked #4 on Affordance Recognition on HICO-DET
no code implementations • 8 Mar 2021 • Qing Li, Xiaojiang Peng, Yu Qiao, Qi Hao
The multi-label learning module leverages a memory feature bank and assigns each image with a multi-label vector based on the similarities between the image and feature bank.
no code implementations • 27 Dec 2020 • Hengshun Zhou, Debin Meng, Yuanyuan Zhang, Xiaojiang Peng, Jun Du, Kai Wang, Yu Qiao
The audio-video based emotion recognition aims to classify a given video into basic emotions.
Facial Expression Recognition (FER) Video Emotion Recognition
no code implementations • 18 Dec 2020 • Kai Wang, Yuxin Gu, Xiaojiang Peng, Panpan Zhang, Baigui Sun, Hao Li
The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which pose an evident challenge for adapting the FER model trained on one dataset to another one.
Facial Expression Recognition Facial Expression Recognition (FER)
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.
Ranked #22 on Multi-Label Classification on MS-COCO
1 code implementation • ECCV 2020 • Xiaojiang Peng, Kai Wang, Zhaoyang Zeng, Qing Li, Jianfei Yang, Yu Qiao
Specifically, this plug-and-play AFM first leverages a \textit{group-to-attend} module to construct groups and assign attention weights for group-wise samples, and then uses a \textit{mixup} module with the attention weights to interpolate massive noisy-suppressed samples.
4 code implementations • ECCV 2020 • Zhi Hou, Xiaojiang Peng, Yu Qiao, DaCheng Tao
The integration of decomposition and composition enables VCL to share object and verb features among different HOI samples and images, and to generate new interaction samples and new types of HOI, and thus largely alleviates the long-tail distribution problem and benefits low-shot or zero-shot HOI detection.
Ranked #3 on Affordance Recognition on HICO-DET(Unknown Concepts)
no code implementations • 7 Mar 2020 • Wen Wang, Xiaojiang Peng, Yanzhou Su, Yu Qiao, Jian Cheng
Video action anticipation aims to predict future action categories from observed frames.
2 code implementations • CVPR 2020 • Kai Wang, Xiaojiang Peng, Jianfei Yang, Shijian Lu, Yu Qiao
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators.
Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 21 Jan 2020 • Wen Wang, Xiaojiang Peng, Yu Qiao, Jian Cheng
Online action detection (OAD) is a practical yet challenging task, which has attracted increasing attention in recent years.
no code implementations • 28 Sep 2019 • Qing Li, Xiaojiang Peng, Yu Qiao, Qiang Peng
In this paper, instead of using a pre-defined graph which is inflexible and may be sub-optimal for multi-label classification, we propose the A-GCN, which leverages the popular Graph Convolutional Networks with an Adaptive label correlation graph to model label dependencies.
no code implementations • 26 Jul 2019 • Qing Li, Xiaojiang Peng, Liangliang Cao, Wenbin Du, Hao Xing, Yu Qiao
Instead of collecting product images by labor-and time-intensive image capturing, we take advantage of the web and download images from the reviews of several e-commerce websites where the images are casually captured by consumers.
no code implementations • 8 Jul 2019 • Kai Wang, Jianfei Yang, Da Guo, Kaipeng Zhang, Xiaojiang Peng, Yu Qiao
Based on our winner solution last year, we mainly explore head features and body features with a bootstrap strategy and two novel loss functions in this paper.
2 code implementations • 29 Jun 2019 • Debin Meng, Xiaojiang Peng, Kai Wang, Yu Qiao
The feature embedding module is a deep Convolutional Neural Network (CNN) which embeds face images into feature vectors.
Ranked #3 on Facial Expression Recognition (FER) on CK+ (Accuracy (7 emotion) metric)
Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 10 May 2019 • Kai Wang, Xiaojiang Peng, Jianfei Yang, Debin Meng, Yu Qiao
Extensive experiments show that our RAN and region biased loss largely improve the performance of FER with occlusion and variant pose.
Ranked #1 on Facial Expression Recognition (FER) on SFEW
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • European Conference on Computer Vision (ECVV 2016) 2016 • Xiaojiang Peng, Cordelia Schmid
We propose a multi-region two-stream R-CNN model for action detection in realistic videos.
Ranked #2 on Action Detection on UCF Sports
no code implementations • 21 Mar 2016 • Guosheng Hu, Xiaojiang Peng, Yongxin Yang, Timothy Hospedales, Jakob Verbeek
To train such networks, very large training sets are needed with millions of labeled images.
no code implementations • CVPR 2014 • Zhuowei Cai, Li-Min Wang, Xiaojiang Peng, Yu Qiao
Kernel average is then applied on these components to produce recognition result.
no code implementations • 18 May 2014 • Xiaojiang Peng, Li-Min Wang, Xingxing Wang, Yu Qiao
Many efforts have been made in each step independently in different scenarios and their effect on action recognition is still unknown.
no code implementations • 2 Sep 2013 • Xiaojiang Peng, Qiang Peng, Yu Qiao, Junzhou Chen, Mehtab Afzal
Many efforts have been devoted to develop alternative methods to traditional vector quantization in image domain such as sparse coding and soft-assignment.