no code implementations • ECCV 2020 • Lida Li, Kun Wang, Shuai Li, Xiangchu Feng, Lei Zhang
The 2D convolutional (Conv2d) layer is the fundamental element to a deep convolutional neural network (CNN).
no code implementations • ACL 2022 • Yubo Ma, Zehao Wang, Mukai Li, Yixin Cao, Meiqi Chen, Xinze Li, Wenqi Sun, Kunquan Deng, Kun Wang, Aixin Sun, Jing Shao
Events are fundamental building blocks of real-world happenings.
no code implementations • 27 Nov 2023 • Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di wu
We seminally propose the concept of Shock Absorber (a type of perturbation) that enhances the robustness and stability of the original graphs against changes in an adversarial training fashion.
no code implementations • 16 Nov 2023 • Yuhan Sun, Mukai Li, Yixin Cao, Kun Wang, Wenxiao Wang, Xingyu Zeng, Rui Zhao
In response, we introduce ControlPE (Continuously Controllable Prompt Engineering).
no code implementations • 11 Oct 2023 • Yuhe Liu, Changhua Pei, Longlong Xu, Bohan Chen, Mingze Sun, Zhirui Zhang, Yongqian Sun, Shenglin Zhang, Kun Wang, Haiming Zhang, Jianhui Li, Gaogang Xie, Xidao Wen, Xiaohui Nie, Dan Pei
Furthermore, a comprehensive benchmark is required to steer the optimization of LLMs tailored for AIOps.
no code implementations • 18 Sep 2023 • Tianyi Song, Jiuxin Cao, Kun Wang, Bo Liu, Xiaofeng Zhang
The current state-of-the-art method combines the features of historical captions, historical frames, and the current captions as conditions for generating the current frame.
no code implementations • 31 Aug 2023 • Si Liu, Chen Gao, Yuan Chen, Xingyu Peng, Xianghao Kong, Kun Wang, Runsheng Xu, Wentao Jiang, Hao Xiang, Jiaqi Ma, Miao Wang
Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue.
no code implementations • 19 Aug 2023 • Kun Wang, Zhiqiang Yan, Huang Tian, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang
Neural Radiance Fields (NeRF) have shown promise in generating realistic novel views from sparse scene images.
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.
no code implementations • 13 Jun 2023 • Lan Wang, Ruiling He, Lili Zhao, Jia Wang, Zhengzi Geng, Tao Ren, Guo Zhang, Peng Zhang, Kaiqiang Tang, Chaofei Gao, Fei Chen, Liting Zhang, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Muhan Lv, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Yunfang Liu, Kun Wang, Meiqin Su, Li Bian, Ping An, Xin Zhang, Linxue Qian, Shao Li, Xiaolong Qi
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
no code implementations • 8 Jun 2023 • Kun Wang, Zhiqiang Yan, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang
Our key contributions are: (1) We parameterize the geometry and appearance of the object using a multi-scale global feature extractor, which avoids frequent point-wise feature retrieval and camera dependency.
no code implementations • 8 Jun 2023 • Kun Wang, Tao Meng, Jiakun Lei, Weijia Wang
In order to address this issue, we propose a control strategy based on control barrier functions, summarized as "safety check on kinematics" and "velocity tracking on dynamics" approach.
no code implementations • 31 May 2023 • Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Shujian Sun
Further, the basic intermittent attitude controller is extended to a "constrained version" by introducing a strictly bounded virtual control law and an input saturation compensation auxiliary system.
no code implementations • 31 May 2023 • Jiakun Lei, Tao Meng, Yang Zhu, Kun Wang, Weijia Wang
To tackle this problem, we propose a modified framework called Compatible Performance Control (CPC), which integrates the Prescribed Performance Control (PPC) scheme with a contradiction detection and alleviation strategy.
no code implementations • 30 May 2023 • Huahui Yi, Ziyuan Qin, Wei Xu, Miaotian Guo, Kun Wang, Shaoting Zhang, Kang Li, Qicheng Lao
To achieve this, we propose a Concept Embedding Search (ConES) approach by optimizing prompt embeddings -- without the need of the text encoder -- to capture the 'concept' of the image modality through a variety of task objectives.
no code implementations • 17 May 2023 • Guiyu Zhao, Bo Qiu, A-Li Luo, XIAOYU GUO, Lin Yao, Kun Wang, Yuanbo Liu
The Wide-field Infrared Survey Explorer (WISE) has detected hundreds of millions of sources over the entire sky.
no code implementations • 12 May 2023 • Zhengqing Yuan, Huiwen Xue, Xinyi Wang, Yongming Liu, Zhuanzhe Zhao, Kun Wang
However, training models on such a large scale is challenging, and finding datasets that match the model's scale is often difficult.
1 code implementation • CVPR 2023 • Zeren Chen, Gengshi Huang, Wei Li, Jianing Teng, Kun Wang, Jing Shao, Chen Change Loy, Lu Sheng
In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR.
no code implementations • 23 Mar 2023 • Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
To construct a representative synthetic training dataset, we maximize the diversity of the selected images via a sample-based and cluster-based method.
no code implementations • 9 Mar 2023 • Yi-Rui Yang, Kun Wang, Wu-Jun Li
Based on ConSpar, we further propose a novel FL framework called FedREP, which is Byzantine-robust, communication-efficient and privacy-preserving.
no code implementations • 28 Feb 2023 • Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao
Specifically, we first discover the base images which contain the FP of novel categories and select a certain amount of samples from them for the base and novel categories balance.
no code implementations • 21 Feb 2023 • Kun Wang, Zi Wang, Zhang Li, Ang Su, Xichao Teng, Minhao Liu, Qifeng Yu
Oriented object detection is one of the most fundamental and challenging tasks in remote sensing, aiming at locating the oriented objects of numerous predefined object categories.
no code implementations • 20 Nov 2022 • Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang
Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation.
no code implementations • 10 Nov 2022 • Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Zhonghe Jin
The prescribed performance control (PPC) scheme is often employed for the control with guaranteed performance.
no code implementations • 22 Oct 2022 • Zhiying Xu, Jiafan Xu, Hongding Peng, Wei Wang, Xiaoliang Wang, Haoran Wan, Haipeng Dai, Yixu Xu, Hao Cheng, Kun Wang, Guihai Chen
Deep learning models rely on highly optimized tensor libraries for efficient inference on heterogeneous hardware.
1 code implementation • 22 Oct 2022 • Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao
Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.
no code implementations • 13 Sep 2022 • Kun Wang, William R. Johnson III, Shiyang Lu, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Mridul Aanjaneya, Kostas Bekris
This strategy is based on a differentiable physics engine that can be trained given limited data from a real robot.
no code implementations • 29 May 2022 • Shiyang Lu, William R. Johnson III, Kun Wang, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Kostas Bekris
To ensure that the pose estimates of rigid elements are physically feasible, i. e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization.
no code implementations • 8 May 2022 • Xueyuan Duan, Yu Fu, Kun Wang
To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method based on mul-ti-scale residual features of network traffic is proposed.
no code implementations • COLING 2022 • Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang
In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improves existing state-of-the-art (SOTA) methods upon two aspects.
no code implementations • 12 Apr 2022 • Haonan Qiu, Siyu Chen, Bei Gan, Kun Wang, Huafeng Shi, Jing Shao, Ziwei Liu
Notably, our method is also validated to be robust to choices of majority and minority forgery approaches.
no code implementations • 18 Mar 2022 • Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li, Jian Yang
To deal with the PDC task, we train a deep network that takes both depth and image as inputs for the dense panoramic depth recovery.
no code implementations • 18 Mar 2022 • Lida Li, Shuai Li, Kun Wang, Xiangchu Feng, Lei Zhang
2D convolution (Conv2d), which is responsible for extracting features from the input image, is one of the key modules of a convolutional neural network (CNN).
2 code implementations • 15 Mar 2022 • Yuanhan Zhang, Qinghong Sun, Yichun Zhou, Zexin He, Zhenfei Yin, Kun Wang, Lu Sheng, Yu Qiao, Jing Shao, Ziwei Liu
This work thus proposes a novel active learning framework for realistic dataset annotation.
Ranked #1 on
Image Classification
on Food-101
(using extra training data)
no code implementations • 28 Feb 2022 • Kun Wang, Mridul Aanjaneya, Kostas Bekris
A model of NASA's icosahedron SUPERballBot on MuJoCo is used as the ground truth system to collect training data.
1 code implementation • ACL 2022 • Yubo Ma, Zehao Wang, Yixin Cao, Mukai Li, Meiqi Chen, Kun Wang, Jing Shao
We have conducted extensive experiments on three benchmarks, including both sentence- and document-level EAE.
1 code implementation • NeurIPS 2021 • Yuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting shao, Kun Wang, Lei He
In this work, we pioneer to study deep learning for dental forensic identification based on panoramic radiographs.
no code implementations • 16 Nov 2021 • Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.
no code implementations • 11 Oct 2021 • Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang
For the phoneme encoder, based on the analysis that same phonemes corresponding to varying pitches can produce similar pronunciations, this encoder is followed by an adversarially trained pitch classifier to enforce the identical phonemes with different pitches mapping into the same phoneme feature space.
no code implementations • 30 Aug 2021 • Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He
Different from single object reconstruction from photos, this task has the unique challenge of constructing multiple objects at high resolutions.
1 code implementation • 22 Aug 2021 • Zhengyong Wang, Liquan Shen, Mei Yu, Kun Wang, Yufei Lin, Mai Xu
However, these methods ignore the significant domain gap between the synthetic and real data (i. e., interdomain gap), and thus the models trained on synthetic data often fail to generalize well to real underwater scenarios.
2 code implementations • ICCV 2021 • Kun Wang, Zhenyu Zhang, Zhiqiang Yan, Xiang Li, Baobei Xu, Jun Li, Jian Yang
Monocular depth estimation aims at predicting depth from a single image or video.
1 code implementation • 4 Aug 2021 • Suofei Zhang, Zirui Yin, Xiofu Wu, Kun Wang, Quan Zhou, Bin Kang
In this paper, we propose a lightweight Feature Pyramid Branch (FPB) to extract features from different layers of networks and aggregate them in a bidirectional pyramid structure.
Ranked #6 on
Person Re-Identification
on CUHK03 labeled
no code implementations • 29 Jul 2021 • Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang
However, blurry guidance in the image and unclear structure in the depth still impede the performance of the image guided frameworks.
Ranked #2 on
Depth Completion
on KITTI Depth Completion
no code implementations • 24 May 2021 • Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao
This paper studies \emph{differential privacy (DP)} and \emph{local differential privacy (LDP)} in cascading bandits.
no code implementations • 17 May 2021 • Jonas Kornprobst, Kun Wang, Gerhard Hamberger, Thomas F. Eibert
The wide half power beamwidth is achieved by suitably designed parasitic patches for the first resonant mode.
no code implementations • 17 Apr 2021 • Kun Wang, Canzhe Zhao, Shuai Li, Shuo Shao
We propose the novel \emph{conservative contextual combinatorial cascading bandit ($C^4$-bandit)}, a cascading online learning game which incorporates the conservative mechanism.
1 code implementation • 5 Feb 2021 • Hanqing Chao, Kun Wang, Yiwei He, Junping Zhang, Jianfeng Feng
In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
no code implementations • 2 Feb 2021 • Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He
Second, we can largely boost the robustness of existing ConvNets, proved by: (i) testing on scans with synthetic pathologies, and (ii) training and evaluation on scans of different scanning setups across datasets.
1 code implementation • 28 Dec 2020 • Kun Wang, Zhixin Song, Xuanqiang Zhao, Zihe Wang, Xin Wang
Firstly, it decomposes a positive map into a combination of quantum operations implementable on near-term quantum devices.
Quantum Physics Strongly Correlated Electrons
no code implementations • 23 Dec 2020 • Jiawei Yang, Yuan Liang, Yao Zhang, Weinan Song, Kun Wang, Lei He
The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines.
no code implementations • 10 Nov 2020 • Kun Wang, Mridul Aanjaneya, Kostas Bekris
The results indicate that only 0. 25\% of ground truth data are needed to train a policy that works on the ground truth system when the differentiable engine is used for training against training the policy directly on the ground truth system.
no code implementations • 9 Nov 2020 • Kun Wang, Mridul Aanjaneya, Kostas Bekris
We propose a novel differentiable physics engine for system identification of complex spring-rod assemblies.
1 code implementation • EMNLP 2020 • Dandan Huang, Leyang Cui, Sen yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang
Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years.
no code implementations • 6 Oct 2020 • Yanchang Gao, Gang Ni, Kun Wang, Yiqing Liu, Chong He, Ronghong Jin, Xianling Liang
The timemodulated module is implemented by adding periodic phase modulation to 2-bit phase shifters, which is simpler without performance loss compared to existing SSB time-modulated method.
no code implementations • 13 Jun 2020 • Shengyun Peng, Yunxuan Yu, Kun Wang, Lei He
Specifically, a target object is defined by a bounding box center, tracking offset, and object size.
no code implementations • L4DC 2020 • Kun Wang, Mridul Aanjaneya, Kostas Bekris
We propose a novel differentiable physics engine for system identification of complex spring-rod assemblies.
2 code implementations • 13 Apr 2020 • Kun Wang, Jun He, Lei Zhang
Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation.
no code implementations • 13 Apr 2020 • Kun Wang, WaiChing Sun, Qiang Du
The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification.
no code implementations • 18 Mar 2020 • Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He
In this paper, we propose a framework, named Oral-3D, to reconstruct the 3D oral cavity from a single PX image and prior information of the dental arch.
no code implementations • ECCV 2020 • Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, Xiaogang Wang
Then this domain-vector is used to encode the features from another domain through a conditional normalization, resulting in different domains' features carrying the same domain attribute.
Ranked #1 on
Unsupervised Domain Adaptation
on SIM10K to BDD100K
no code implementations • 19 Feb 2020 • Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He
The encoder-decoder network is widely used to learn deep feature representations from pixel-wise annotations in biomedical image analysis.
no code implementations • 3 Feb 2020 • Xinhe Jiang, Kun Wang, Kaiyi Qian, Zhaozhong Chen, Zhiyu Chen, Liangliang Lu, Lijun Xia, Fangmin Song, Shining Zhu, Xiaosong Ma
We experimentally obtain the scaling parameter of $r=-0. 88\pm$0. 03 and $-0. 78\pm$0. 07 for nonadaptive and adaptive strategies, respectively.
Quantum Physics Optics
no code implementations • 7 Jan 2020 • Yinqiu Liu, Kai Qian, Jianli Chen, Kun Wang, Lei He
As an emerging technology, blockchain has achieved great success in numerous application scenarios, from intelligent healthcare to smart cities.
Cryptography and Security Distributed, Parallel, and Cluster Computing 68M14 C.2.2
no code implementations • 10 Oct 2019 • Yuan Liang, Weinan Song, J. P. Dym, Kun Wang, Lei He
Label propagation is a popular technique for anatomical segmentation.
no code implementations • 14 May 2019 • Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio
In this work, a sparsity-driven observer (SDO) that can be employed to optimize hardware by use of a stochastic object model describing object sparsity is described and investigated.
no code implementations • 3 May 2019 • Wenmian Yang, Kun Wang, Na Ruan, Wenyuan Gao, Weijia Jia, Wei Zhao, Nan Liu, Yunyong Zhang
Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF).
1 code implementation • NAACL 2019 • Kai Song, Yue Zhang, Heng Yu, Weihua Luo, Kun Wang, Min Zhang
Leveraging user-provided translation to constrain NMT has practical significance.
no code implementations • 24 Mar 2019 • Kun Wang, Jun He, Lei Zhang
Unlike images or videos data which can be easily labeled by human being, sensor data annotation is a time-consuming process.
no code implementations • 8 Mar 2019 • Kun Wang, WaiChing Sun, Qiang Du
We introduce a multi-agent meta-modeling game to generate data, knowledge, and models that make predictions on constitutive responses of elasto-plastic materials.
no code implementations • 24 Oct 2018 • Kun Wang, WaiChing Sun
This paper presents a new meta-modeling framework to employ deep reinforcement learning (DRL) to generate mechanical constitutive models for interfaces.
no code implementations • 15 Aug 2018 • Kun Wang
Ricean channel model is widely used in wireless communications to characterize the channels with a line-of-sight path.
no code implementations • 8 Apr 2018 • Xiaogang Cheng, Guoqing Liu, Anders Hedman, Kun Wang, Hai-Bo Li
We assume fog and haze cause blurred images and that fog and haze can be considered as a piecewise stationary signal.
no code implementations • ICCV 2017 • Wanli Ouyang, Kun Wang, Xin Zhu, Xiaogang Wang
In this CC-Net, there are many cascade stages.
1 code implementation • ICCV 2017 • Yikang Li, Wanli Ouyang, Bolei Zhou, Kun Wang, Xiaogang Wang
Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generated on top of objects detected in an image with their pairwise relationship predicted, while region captioning gives a language description of the objects, their attributes, relations, and other context information.
Ranked #2 on
Object Detection
on Visual Genome
1 code implementation • 8 Oct 2016 • Xingyu Zeng, Wanli Ouyang, Junjie Yan, Hongsheng Li, Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin Yang, Zhe Wang, Hui Zhou, Xiaogang Wang
The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO.