no code implementations • COLING 2022 • Zhihua Su, Qiang Zhou
We propose a speaker clustering model for textual dialogues, which groups the utterances of a multi-party dialogue without speaker annotations, so that the actual speakers are identical inside each cluster.
no code implementations • CCL 2020 • Haocong Shan, Qiang Zhou
给定包含主旨概括句的汉语句群, 针对该句群的内部结构标注是基于语言学的分析结果, 而阅读句群时的眼动轨迹则蕴含着人的心理认知, 两者的信息融合和内在关联性分析是该文主要工作。该文使用基于径向基函数支持向量机和递归特征消除的分类模型, 根据标点小句片段对应的眼动指标数据预测该片段是否为包含主旨内容的关键信息, 达到了0. 76的准确率, 并通过分析关键片段上眼动数据的分布特点, 提取出对句群主旨概括信息区分度较好的眼动指标。
no code implementations • 28 May 2024 • Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras
We thus propose an automated pipeline to collect a high-quality dataset for code explanation and refinement by generating a number of explanations and refinement trajectories and filtering via execution verification.
1 code implementation • 21 May 2024 • Zhiyu Tan, Mengping Yang, Luozheng Qin, Hao Yang, Ye Qian, Qiang Zhou, Cheng Zhang, Hao Li
Moreover, the model capacity of the text encoder from CLIP is relatively limited compared to Large Language Models (LLMs), which offer multilingual input, accommodate longer context, and achieve superior text representation.
1 code implementation • 28 Jan 2024 • Shaofeng Zhang, Jinfa Huang, Qiang Zhou, Zhibin Wang, Fan Wang, Jiebo Luo, Junchi Yan
At inference, we generate images with arbitrary expansion multiples by inputting an anchor image and its corresponding positional embeddings.
no code implementations • 4 Jan 2024 • Rui Ma, Qiang Zhou, Bangjun Xiao, Yizhu Jin, Daquan Zhou, Xiuyu Li, Aishani Singh, Yi Qu, Kurt Keutzer, Xiaodong Xie, Jingtong Hu, Zhen Dong, Shanghang Zhang
Copyright is a legal right that grants creators the exclusive authority to reproduce, distribute, and profit from their creative works.
no code implementations • 19 Dec 2023 • Yuang Liu, Jing Wang, Qiang Zhou, Fan Wang, Jun Wang, Wei zhang
Numerous self-supervised learning paradigms, such as contrastive learning and masked image modeling, have been proposed to acquire powerful and general representations from unlabeled data.
no code implementations • 23 Nov 2023 • Jing Wang, Yuang Liu, Qiang Zhou, Fan Wang
Few-shot learning is a promising way for reducing the label cost in new categories adaptation with the guidance of a small, well labeled support set.
2 code implementations • 12 Nov 2023 • Qiang Zhou, Zhibin Wang, Wei Chu, Yinghui Xu, Hao Li, Yuan Qi
Our experiments demonstrate that preserving the positional information of visual embeddings through the pool-adapter is particularly beneficial for tasks like visual grounding.
Ranked #67 on Visual Question Answering on MM-Vet
1 code implementation • NeurIPS 2023 • Qiang Zhou, Weize Li, Lihan Jiang, Guoliang Wang, Guyue Zhou, Shanghang Zhang, Hao Zhao
Furthermore, we provide an open-source benchmark library, including dataset and baseline methods that cover 8 anomaly detection paradigms, to facilitate future research and application in this domain.
Ranked #2 on Anomaly Detection on PAD Dataset
no code implementations • 4 Oct 2023 • Hongxin Ding, Peinie Zou, Zhiyuan Wang, Junfeng Zhao, Yasha Wang, Qiang Zhou
Extracting medical knowledge from healthcare texts enhances downstream tasks like medical knowledge graph construction and clinical decision-making.
no code implementations • 14 Aug 2023 • Chaohui Yu, Qiang Zhou, Zhibin Wang, Fan Wang
Second, we propose an align-guided contrastive loss to refine the alignment of vision and text embeddings.
no code implementations • 4 Aug 2023 • Qiang Zhou, Chaohui Yu, Jingliang Li, Yuang Liu, Jing Wang, Zhibin Wang
to provide additional consistency constraints, which grows GPU memory consumption and complicates the model's structure and training pipeline.
1 code implementation • 3 Aug 2023 • Qiang Zhou, Chaohui Yu, Shaofeng Zhang, Sitong Wu, Zhibing Wang, Fan Wang
To this end, we propose to extract features corresponding to regional objects as soft prompts for LLM, which provides a straightforward and scalable approach and eliminates the need for LLM fine-tuning.
no code implementations • 3 Aug 2023 • Yuang Liu, Qiang Zhou, Jing Wang, Fan Wang, Jun Wang, Wei zhang
Vision transformers (ViT) usually extract features via forwarding all the tokens in the self-attention layers from top to toe.
no code implementations • 27 Jul 2023 • Jingliang Li, Qiang Zhou, Chaohui Yu, Zhengda Lu, Jun Xiao, Zhibin Wang, Fan Wang
To make the constructed volumes as close as possible to the surfaces of objects in the scene and the rendered depth more accurate, we propose to perform depth prediction and radiance field reconstruction simultaneously.
no code implementations • 26 Jul 2023 • Chaohui Yu, Qiang Zhou, Jingliang Li, Zhe Zhang, Zhibin Wang, Fan Wang
To better utilize the sparse 3D points, we propose an efficient point cloud guidance loss to adaptively drive the NeRF's geometry to align with the shape of the sparse 3D points.
1 code implementation • CVPR 2023 • Xiaoxue Chen, Yuhang Zheng, Yupeng Zheng, Qiang Zhou, Hao Zhao, Guyue Zhou, Ya-Qin Zhang
We showcase the effectiveness of DPFs using two substantially different tasks: high-level semantic parsing and low-level intrinsic image decomposition.
no code implementations • 1 Mar 2023 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Fan Wang
In this paper, we propose an end-to-end framework for oriented object detection, which simplifies the model pipeline and obtains superior performance.
no code implementations • CVPR 2023 • Chaohui Yu, Qiang Zhou, Jingliang Li, Jianlong Yuan, Zhibin Wang, Fan Wang
In this work, we propose a novel and data-efficient framework for WILSS, named FMWISS.
no code implementations • 27 Feb 2023 • Qiang Zhou, Yuang Liu, Chaohui Yu, Jingliang Li, Zhibin Wang, Fan Wang
Instead of relabeling each dataset with the unified taxonomy, a category-guided decoding module is designed to dynamically guide predictions to each datasets taxonomy.
no code implementations • 7 Sep 2022 • Qiang Zhou, Chaohui Yu, Hao Luo, Zhibin Wang, Hao Li
Specifically, MimCo takes a pre-trained contrastive learning model as the teacher model and is pre-trained with two types of learning targets: patch-level and image-level reconstruction losses.
no code implementations • 1 Jun 2022 • Yongtao Ge, Qiang Zhou, Xinlong Wang, Zhibin Wang, Hao Li, Chunhua Shen
Point annotations are considerably more time-efficient than bounding box annotations.
no code implementations • 28 May 2022 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Hao Li
To tackle this problem, we propose a purely angle-free framework for rotated object detection, called Point RCNN, which mainly consists of PointRPN and PointReg.
no code implementations • 4 May 2022 • Zhen Dong, Kaicheng Zhou, Guohao Li, Qiang Zhou, Mingfei Guo, Bernard Ghanem, Kurt Keutzer, Shanghang Zhang
Neural architecture search (NAS) has shown great success in the automatic design of deep neural networks (DNNs).
no code implementations • 13 Apr 2022 • Yaojie Hu, Xingjian Shi, Qiang Zhou, Lee Pike
We introduce NSEdit (neural-symbolic edit), a novel Transformer-based code repair method.
no code implementations • 14 Feb 2022 • Junde Wu, Huihui Fang, Fei Li, Huazhu Fu, Fengbin Lin, Jiongcheng Li, Lexing Huang, Qinji Yu, Sifan Song, Xinxing Xu, Yanyu Xu, Wensai Wang, Lingxiao Wang, Shuai Lu, Huiqi Li, Shihua Huang, Zhichao Lu, Chubin Ou, Xifei Wei, Bingyuan Liu, Riadh Kobbi, Xiaoying Tang, Li Lin, Qiang Zhou, Qiang Hu, Hrvoje Bogunovic, José Ignacio Orlando, Xiulan Zhang, Yanwu Xu
However, although numerous algorithms are proposed based on fundus images or OCT volumes in computer-aided diagnosis, there are still few methods leveraging both of the modalities for the glaucoma assessment.
1 code implementation • 30 Aug 2021 • Gui-Song Xia, Jian Ding, Ming Qian, Nan Xue, Jiaming Han, Xiang Bai, Michael Ying Yang, Shengyang Li, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, Liangpei Zhang, Qiang Zhou, Chao-hui Yu, Kaixuan Hu, Yingjia Bu, Wenming Tan, Zhe Yang, Wei Li, Shang Liu, Jiaxuan Zhao, Tianzhi Ma, Zi-han Gao, Lingqi Wang, Yi Zuo, Licheng Jiao, Chang Meng, Hao Wang, Jiahao Wang, Yiming Hui, Zhuojun Dong, Jie Zhang, Qianyue Bao, Zixiao Zhang, Fang Liu
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in aerial images.
1 code implementation • CVPR 2022 • Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu
By comprehensively investigating these GE-ViTs and comparing with their corresponding CNN models, we observe: 1) For the enhanced model, larger ViTs still benefit more for the OOD generalization.
1 code implementation • ICCV 2021 • Yijia Weng, He Wang, Qiang Zhou, Yuzhe Qin, Yueqi Duan, Qingnan Fan, Baoquan Chen, Hao Su, Leonidas J. Guibas
For the first time, we propose a unified framework that can handle 9DoF pose tracking for novel rigid object instances as well as per-part pose tracking for articulated objects from known categories.
no code implementations • CVPR 2021 • Qiang Zhou, Shiyin Wang, Yitong Wang, Zilong Huang, Xinggang Wang
Besides, an Amodal Human Perception dataset (AHP) is collected to settle the task of human de-occlusion.
1 code implementation • CVPR 2021 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Qi Qian, Hao Li
To alleviate the confirmation bias problem and improve the quality of pseudo annotations, we further propose a co-rectify scheme based on Instant-Teaching, denoted as Instant-Teaching$^*$.
Ranked #12 on Semi-Supervised Object Detection on COCO 100% labeled data (using extra training data)
no code implementations • 28 Jan 2021 • Qiang Zhou, Chaohui Yu, Chunhua Shen, Zhibin Wang, Hao Li
On the COCO dataset, our simple design achieves superior performance compared to both the FCOS baseline detector with NMS post-processing and the recent end-to-end NMS-free detectors.
no code implementations • 18 Jan 2021 • Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao, Qiuhong Wang, Xiao Zhang
Intuitively, the potential crowd flow of the new coming site can be implied by exploring the nearby sites.
no code implementations • 1 Jan 2021 • Yong Geng, Heng Zhou, Wenwen Cui, Xinjie Han, Qiang Zhang, Boyuan Liu, Guangwei Deng, Qiang Zhou, Kun Qiu
Dissipative Kerr soliton microcomb has been recognized as a promising on-chip multi-wavelength laser source for fiber optical communications, as its comb lines possess frequency and phase stability far beyond independent lasers.
no code implementations • 5 Nov 2020 • Jingjing Cao, Fukang Guo, Xin Lai, Qiang Zhou, Jinshan Dai
With the propagation of sensor devices applied in smart home, activity recognition has ignited huge interest and most existing works assume that there is only one habitant.
1 code implementation • 13 Apr 2020 • Jingjing Gu, Qiang Zhou, Jingyuan Yang, Yanchi Liu, Fuzhen Zhuang, Yanchao Zhao, Hui Xiong
Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility.
no code implementations • CVPR 2020 • Zhuoqian Yang, Wentao Zhu, Wayne Wu, Chen Qian, Qiang Zhou, Bolei Zhou, Chen Change Loy
We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target person.
1 code implementation • medRxiv 2020 • Chuansheng Zheng, Xianbo Deng, Qing Fu, Qiang Zhou, Jiapei Feng, Hui Ma, Wenyu Liu, Xinggang Wang
Our weakly-supervised deep learning model can accurately predict the COVID-19 infectious probability in chest CT volumes without the need for annotating the lesions for training.
1 code implementation • ICCV 2019 • Keqiang Sun, Wayne Wu, Tinghao Liu, Shuo Yang, Quan Wang, Qiang Zhou, Zuochang Ye, Chen Qian
A structure predictor is proposed to predict the missing face structural information temporally, which serves as a geometry prior.
1 code implementation • 2 Jul 2019 • Qiang Zhou, Zilong Huang, Lichao Huang, Yongchao Gong, Han Shen, Chang Huang, Wenyu Liu, Xinggang Wang
Video object segmentation (VOS) aims at pixel-level object tracking given only the annotations in the first frame.
Ranked #1 on Visual Object Tracking on YouTube-VOS 2018 (Jaccard (Seen) metric)
no code implementations • 6 Jun 2019 • Qiang Zhou, Xin Li
In this paper, we introduce the STN-Homography model to directly estimate the homography matrix between image pair.
2 code implementations • CVPR 2018 • Wayne Wu, Chen Qian, Shuo Yang, Quan Wang, Yici Cai, Qiang Zhou
By utilising boundary information of 300-W dataset, our method achieves 3. 92% mean error with 0. 39% failure rate on COFW dataset, and 1. 25% mean error on AFLW-Full dataset.
Ranked #4 on Face Alignment on AFLW-19 (using extra training data)
no code implementations • 8 Feb 2018 • Jianlei Yang, Xueyan Wang, Qiang Zhou, Zhaohao Wang, Hai, Li, Yiran Chen, Weisheng Zhao
Circuit obfuscation is a frequently used approach to conceal logic functionalities in order to prevent reverse engineering attacks on fabricated chips.
Emerging Technologies Cryptography and Security
no code implementations • COLING 2016 • Xian-Ling Mao, Yi-Jing Hao, Qiang Zhou, Wen-Qing Yuan, Liner Yang, He-Yan Huang
Recently, topic modeling has been widely applied in data mining due to its powerful ability.
no code implementations • PACLIC 2015 • Miao Fan, Qiang Zhou, Thomas Fang Zheng
In this paper, we propose a new paradigm named distantly supervised entity linking (DSEL), in the sense that the disambiguated entities that belong to a huge knowledge repository (Freebase) are automatically aligned to the corresponding descriptive webpages (Wiki pages).
no code implementations • 10 May 2015 • Miao Fan, Qiang Zhou, Andrew Abel, Thomas Fang Zheng, Ralph Grishman
This paper contributes a novel embedding model which measures the probability of each belief $\langle h, r, t, m\rangle$ in a large-scale knowledge repository via simultaneously learning distributed representations for entities ($h$ and $t$), relations ($r$), and the words in relation mentions ($m$).
no code implementations • 7 Apr 2015 • Miao Fan, Qiang Zhou, Thomas Fang Zheng, Ralph Grishman
Traditional way of storing facts in triplets ({\it head\_entity, relation, tail\_entity}), abbreviated as ({\it h, r, t}), makes the knowledge intuitively displayed and easily acquired by mankind, but hardly computed or even reasoned by AI machines.
no code implementations • 27 Mar 2015 • Miao Fan, Qiang Zhou, Thomas Fang Zheng
This paper considers the problem of knowledge inference on large-scale imperfect repositories with incomplete coverage by means of embedding entities and relations at the first attempt.
no code implementations • 17 Nov 2014 • Miao Fan, Deli Zhao, Qiang Zhou, Zhiyuan Liu, Thomas Fang Zheng, Edward Y. Chang
The essence of distantly supervised relation extraction is that it is an incomplete multi-label classification problem with sparse and noisy features.