no code implementations • 20 Nov 2023 • Zimu Wang, Wei Wang, Qi Chen, Qiufeng Wang, Anh Nguyen
Deep learning-based natural language processing (NLP) models, particularly pre-trained language models (PLMs), have been revealed to be vulnerable to adversarial attacks.
no code implementations • 31 Oct 2023 • Yuqi Wang, Zeqiang Wang, Wei Wang, Qi Chen, Kaizhu Huang, Anh Nguyen, Suparna De
In the era of the Internet of Things (IoT), the retrieval of relevant medical information has become essential for efficient clinical decision-making.
1 code implementation • 6 Oct 2023 • Yinda Chen, Wei Huang, Shenglong Zhou, Qi Chen, Zhiwei Xiong
By extracting semantic information from unlabeled data, self-supervised methods can improve the performance of downstream tasks, among which the mask image model (MIM) has been widely used due to its simplicity and effectiveness in recovering original information from masked images.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
1 code implementation • NeurIPS 2023 • Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui
We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions.
no code implementations • 31 Aug 2023 • Qi Chen, Wei Huang, Yueyi Zhang, Zhiwei Xiong
In the second stage, we improve model generalizability on target data by regenerating square masks to get high-quality pseudo labels.
1 code implementation • 31 Aug 2023 • Changli Wu, Yiwei Ma, Qi Chen, Haowei Wang, Gen Luo, Jiayi Ji, Xiaoshuai Sun
In 3D Referring Expression Segmentation (3D-RES), the earlier approach adopts a two-stage paradigm, extracting segmentation proposals and then matching them with referring expressions.
no code implementations • 21 Aug 2023 • Qi Chen, Dexi Liu
The combination of chain-of-thought (CoT) prompting and Large Language Models (LLMs) is employed and get the SOTA performance on various NLP tasks, especially on text generation tasks.
no code implementations • 19 Aug 2023 • Yinda Chen, Wei Huang, Xiaoyu Liu, Shiyu Deng, Qi Chen, Zhiwei Xiong
Instance segmentation in electron microscopy (EM) volumes is tough due to complex shapes and sparse annotations.
1 code implementation • 16 Aug 2023 • Qi Chen, Chaorui Deng, Zixiong Huang, BoWen Zhang, Mingkui Tan, Qi Wu
In this paper, we propose to evaluate text-to-image generation performance by directly estimating the likelihood of the generated images using a pre-trained likelihood-based text-to-image generative model, i. e., a higher likelihood indicates better perceptual quality and better text-image alignment.
1 code implementation • ICCV 2023 • Chaorui Deng, Qi Chen, Pengda Qin, Da Chen, Qi Wu
In text-video retrieval, recent works have benefited from the powerful learning capabilities of pre-trained text-image foundation models (e. g., CLIP) by adapting them to the video domain.
no code implementations • 4 Aug 2023 • Qi Chen, Dexi Liu
This innovative structure reduces the excessive reliance on pre-trained language models and emphasizes the modeling of structure and local relationships, thereby improving the performance of the model on Chinese financial texts.
no code implementations • 14 Jul 2023 • Qi Chen, Chao Guo
Path integral method in quantum theory provides a new thinking for time dependent option pricing.
no code implementations • 2 Jul 2023 • Sen Pei, Jiaxi Sun, Peng Qin, Qi Chen, Xinglong Wu, Xun Wang
Out-of-distribution (OOD) detection empowers the model trained on the closed set to identify unknown data in the open world.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
1 code implementation • 8 Jun 2023 • Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Anastasis Stathopoulos, Xiaoxiao He, Yuxiao Chen, Di Liu, Qilong Zhangli, Jindong Jiang, Zhaoyang Xia, Akash Srivastava, Dimitris Metaxas
Null-text inversion (NTI) optimizes null embeddings to align the reconstruction and inversion trajectories with larger CFG scales, enabling real image editing with cross-attention control.
1 code implementation • 26 May 2023 • Qi Chen, Yutong Xie, Biao Wu, Minh-Son To, James Ang, Qi Wu
In this paper, we seek to design a report generation model that is able to generate reasonable reports even given different images of various body parts.
1 code implementation • 4 Apr 2023 • Qi Chen, Mario Marchand
We further provide algorithm-dependent generalization bounds for these two settings, where the generalization is characterized by the mutual information between the parameters and the data.
no code implementations • 30 Mar 2023 • Chenpeng Du, Qi Chen, Tianyu He, Xu Tan, Xie Chen, Kai Yu, Sheng Zhao, Jiang Bian
Additionally, we propose a novel method for generating continuous video frames with the DDIM image decoder trained on individual frames, eliminating the need for modelling the joint distribution of consecutive frames directly.
1 code implementation • 17 Mar 2023 • Yidan Zhang, Ting Zhang, Dong Chen, Yujing Wang, Qi Chen, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Mao Yang, Qingmin Liao, Baining Guo
While generative modeling has been ubiquitous in natural language processing and computer vision, its application to image retrieval remains unexplored.
no code implementations • 3 Mar 2023 • Sen Pei, Jingya Yu, Qi Chen, Wozhou He
In this paper, we investigate a novel and practical problem, namely audio beat matching (ABM), which aims to recommend the proper transition time stamps based on the background music.
1 code implementation • 25 Feb 2023 • Jiawei Hou, Qi Chen, Yurong Cheng, Guang Chen, xiangyang xue, Taiping Zeng, Jian Pu
However, there is a lack of underground parking scenario datasets with multiple sensors and well-labeled images that support both SLAM tasks and perception tasks, such as semantic segmentation and parking slot detection.
no code implementations • 15 Feb 2023 • Qi Chen, Chao Guo
Path integral method in quantum mechanics provides a new thinking for barrier option pricing.
no code implementations • 9 Feb 2023 • Qi Chen, Chao Li, Jia Ning, Stephen Lin, Kun He
Inspired by the property that ERFs typically exhibit a Gaussian distribution, we propose a Gaussian Mask convolutional kernel (GMConv) in this work.
1 code implementation • IEEE Transactions on Evolutionary Computation 2023 • Hengzhe Zhang, Aimin Zhou, Qi Chen, Bing Xue, Mengjie Zhang
Ensemble learning methods have been widely used in machine learning in recent years due to their high predictive performance.
no code implementations • 7 Feb 2023 • Xiaohu Tang, Yang Wang, Ting Cao, Li Lyna Zhang, Qi Chen, Deng Cai, Yunxin Liu, Mao Yang
On-device Deep Neural Network (DNN) inference consumes significant computing resources and development efforts.
no code implementations • 30 Jan 2023 • Christian Raymond, Qi Chen, Bing Xue, Mengjie Zhang
Loss function learning is a new meta-learning paradigm that aims to automate the essential task of designing a loss function for a machine learning model.
no code implementations • 11 Nov 2022 • Jinshan Zeng, Yefei Wang, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan YAO
The effectiveness of the proposed model for the zero-shot traditional Chinese font generation is also evaluated in this paper.
1 code implementation • 19 Oct 2022 • Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles Ling, Tal Arbel, Boyu Wang, Christian Gagné
In the upper-level, the fair predictor is updated to be close to all subgroup specific predictors.
1 code implementation • 14 Oct 2022 • Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
More critically, these independent search processes cannot share their learned knowledge (i. e., the distribution of good architectures) with each other and thus often result in limited search results.
no code implementations • 26 Sep 2022 • Qi Chen, Hong-tao Wang, Chao Guo
Path integral method in quantum mechanics provides a new thinking for barrier option pricing.
no code implementations • 19 Sep 2022 • Christian Raymond, Qi Chen, Bing Xue, Mengjie Zhang
In this paper, we develop upon the emerging topic of loss function learning, which aims to learn loss functions that significantly improve the performance of the models trained under them.
1 code implementation • 17 Sep 2022 • Qi Chen, Chaorui Deng, Qi Wu
Our innovative idea is to explore the rich modes in the training caption corpus to learn a set of "mode embeddings", and further use them to control the mode of the generated captions for existing image captioning models.
1 code implementation • 16 Jul 2022 • Yong Guo, Jingdong Wang, Qi Chen, JieZhang Cao, Zeshuai Deng, Yanwu Xu, Jian Chen, Mingkui Tan
Nevertheless, it is hard for existing model compression methods to accurately identify the redundant components due to the extremely large SR mapping space.
1 code implementation • 29 Jun 2022 • Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Moreover, we show that the optimization-induced variants of our models can boost the performance and improve training stability and efficiency as well.
no code implementations • 9 Jun 2022 • Xin Li, Daqi Zhu, Bing Sun, Qi Chen, Wenyang Gan, Zhigang Li
At last, a robust sliding mode controller with continuous model predictive control strategy for the multi-AUV system is developed to achieve leader-follower formation tracking under the presence of bounded flow disturbances, and simulations are implemented to confirm the effectiveness of the proposed method.
1 code implementation • 6 Jun 2022 • Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Allen Sun, Weiwei Deng, Qi Zhang, Mao Yang
To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.
no code implementations • 26 May 2022 • Changjian Shui, Qi Chen, Jiaqi Li, Boyu Wang, Christian Gagné
We consider a fair representation learning perspective, where optimal predictors, on top of the data representation, are ensured to be invariant with respect to different sub-groups.
no code implementations • 8 May 2022 • Harsha Vardhan Simhadri, George Williams, Martin Aumüller, Matthijs Douze, Artem Babenko, Dmitry Baranchuk, Qi Chen, Lucas Hosseini, Ravishankar Krishnaswamy, Gopal Srinivasa, Suhas Jayaram Subramanya, Jingdong Wang
The outcome of the competition was ranked leaderboards of algorithms in each track based on recall at a query throughput threshold.
no code implementations • 19 Apr 2022 • Qi Chen, Sourabh Vora
We propose a simple yet effective proposal-free architecture for lidar panoptic segmentation.
2 code implementations • 1 Apr 2022 • Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Denvy Deng, Qi Zhang, Xing Xie
We perform comprehensive explorations for the optimal conduct of knowledge distillation, which may provide useful insights for the learning of VQ based ANN index.
1 code implementation • CVPR 2022 • Qi Chen, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
Weakly Supervised Semantic Segmentation (WSSS) based on image-level labels has attracted much attention due to low annotation costs.
Ranked #13 on
Weakly-Supervised Semantic Segmentation
on COCO 2014 val
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
no code implementations • 16 Dec 2021 • Qi Chen, Chao Guo
Path integral method in quantum mechanics provides a new thinking for barrier option pricing.
no code implementations • NeurIPS 2021 • Qi Chen, Sourabh Vora, Oscar Beijbom
Recent works recognized lidars as an inherently streaming data source and showed that the end-to-end latency of lidar perception models can be reduced significantly by operating on wedge-shaped point cloud sectors rather then the full point cloud.
no code implementations • CVPR 2022 • Qi Chen, Yuanqing Li, Yuankai Qi, Jiaqiu Zhou, Mingkui Tan, Qi Wu
Existing Voice Cloning (VC) tasks aim to convert a paragraph text to a speech with desired voice specified by a reference audio.
5 code implementations • 17 Nov 2021 • Delv Lin, Qi Chen, Chengyu Zhou, Kun He
Multi-Object Tracking (MOT) has achieved aggressive progress and derived many excellent deep learning trackers.
1 code implementation • NeurIPS 2021 • Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang
It stores the centroid points of the posting lists in the memory and the large posting lists in the disk.
1 code implementation • NeurIPS 2021 • Qi Chen, Changjian Shui, Mario Marchand
We derive a novel information-theoretic analysis of the generalization property of meta-learning algorithms.
no code implementations • 14 Jun 2021 • Qi Chen, Sourabh Vora, Oscar Beijbom
Recent works recognized lidars as an inherently streaming data source and showed that the end-to-end latency of lidar perception models can be reduced significantly by operating on wedge-shaped point cloud sectors rather then the full point cloud.
Ranked #21 on
LIDAR Semantic Segmentation
on nuScenes
1 code implementation • NeurIPS 2021 • Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang
It stores the centroid points of the posting lists in the memory and the large posting lists in the disk.
1 code implementation • CVPR 2021 • Yaofo Chen, Yong Guo, Qi Chen, Minli Li, Wei Zeng, YaoWei Wang, Mingkui Tan
One of the key steps in Neural Architecture Search (NAS) is to estimate the performance of candidate architectures.
no code implementations • 27 Feb 2021 • Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
To this end, we propose a Pareto-Frontier-aware Neural Architecture Generator (NAG) which takes an arbitrary budget as input and produces the Pareto optimal architecture for the target budget.
2 code implementations • 20 Feb 2021 • Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao, Junzhou Huang
To address this issue, we propose a Neural Architecture Transformer++ (NAT++) method which further enlarges the set of candidate transitions to improve the performance of architecture optimization.
1 code implementation • 16 Dec 2020 • Jinshan Zeng, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan YAO
However, these deep generative models may suffer from the mode collapse issue, which significantly degrades the diversity and quality of generated results.
no code implementations • NeurIPS 2020 • Qi Chen, Lin Sun, Ernest Cheung, Alan L. Yuille
We proposed a pair of cross-view transformers to transform the feature maps into the other view and introduce cross-view consistency loss on them.
no code implementations • 22 Nov 2020 • Yihan Zheng, Zhiquan Wen, Mingkui Tan, Runhao Zeng, Qi Chen, YaoWei Wang, Qi Wu
Moreover, to capture the complex logic in a query, we construct a relational graph to represent the visual objects and their relationships, and propose a multi-step reasoning method to progressively understand the complex logic.
Ranked #2 on
Referring Expression Comprehension
on CLEVR-Ref+
no code implementations • 24 Sep 2020 • Jingda Guo, Dominic Carrillo, Sihai Tang, Qi Chen, Qing Yang, Song Fu, Xi Wang, Nannan Wang, Paparao Palacharla
To reduce the amount of transmitted data, feature map based fusion is recently proposed as a practical solution to cooperative 3D object detection by autonomous vehicles.
no code implementations • 30 Jul 2020 • Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, Boyu Wang
We reveal the incoherence between the widely-adopted empirical domain adversarial training and its generally-assumed theoretical counterpart based on $\mathcal{H}$-divergence.
1 code implementation • 10 Jul 2020 • Xuan Shan, Chuanjie Liu, Yiqian Xia, Qi Chen, Yusi Zhang, Kaize Ding, Yaobo Liang, Angen Luo, Yuxiang Luo
Deep matching models aim to facilitate search engines retrieving more relevant documents by mapping queries and documents into semantic vectors in the first-stage retrieval.
no code implementations • 9 Jul 2020 • Xu Ma, Jingda Guo, Sihai Tang, Zhinan Qiao, Qi Chen, Qing Yang, Song Fu
With DCANet, all attention blocks in a CNN model are trained jointly, which improves the ability of attention learning.
2 code implementations • 23 May 2020 • Junxu Cao, Qi Chen, Jun Guo, Ruichao Shi
For object detection, how to address the contradictory requirement between feature map resolution and receptive field on high-resolution inputs still remains an open question.
Ranked #73 on
Object Detection
on COCO test-dev
no code implementations • 31 Mar 2020 • Chendi Rao, JieZhang Cao, Runhao Zeng, Qi Chen, Huazhu Fu, Yanwu Xu, Mingkui Tan
In this paper, we aim to review various adversarial attack and defense methods on chest X-rays.
3 code implementations • CVPR 2020 • Yong Guo, Jian Chen, Jingdong Wang, Qi Chen, JieZhang Cao, Zeshuai Deng, Yanwu Xu, Mingkui Tan
Extensive experiments with paired training data and unpaired real-world data demonstrate our superiority over existing methods.
1 code implementation • CVPR 2020 • Qi Chen, Qi Wu, Rui Tang, Yu-Han Wang, Shuai Wang, Mingkui Tan
To this end, we propose a House Plan Generative Model (HPGM) that first translates the language input to a structural graph representation and then predicts the layout of rooms with a Graph Conditioned Layout Prediction Network (GC LPN) and generates the interior texture with a Language Conditioned Texture GAN (LCT-GAN).
no code implementations • ECCV 2020 • Qi Chen, Lin Sun, Zhixin Wang, Kui Jia, Alan Yuille
Accurate 3D object detection in LiDAR based point clouds suffers from the challenges of data sparsity and irregularities.
Ranked #3 on
3D Object Detection
on KITTI Pedestrians Moderate
1 code implementation • NeurIPS 2019 • Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang
To verify the effectiveness of the proposed strategies, we apply NAT on both hand-crafted architectures and NAS based architectures.
1 code implementation • SCiL 2020 • Hai Hu, Qi Chen, Kyle Richardson, Atreyee Mukherjee, Lawrence S. Moss, Sandra Kuebler
We present a new logic-based inference engine for natural language inference (NLI) called MonaLog, which is based on natural logic and the monotonicity calculus.
1 code implementation • 13 Sep 2019 • Qi Chen
Autonomous vehicles are heavily reliant upon their sensors to perfect the perception of surrounding environments, however, with the current state of technology, the data which a vehicle uses is confined to that from its own sensors.
Ranked #4 on
3D Object Detection
on OPV2V
no code implementations • 4 Jul 2019 • Wenjun Liu, Yuchun Huang, Ying Li, Qi Chen
Specifically, we first propose the Multi-Dilation (MD) module, which can synthesize the crack features of multiple context sizes via dilated convolution with multiple rates.
3 code implementations • 3 Jun 2019 • Jie Ren, Fei Zhou, Xiaoxi Li, Qi Chen, Hongmei Zhang, Shuangge Ma, Yu Jiang, Cen Wu
Existing Bayesian methods for G$\times$E interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences.
Methodology
1 code implementation • 13 May 2019 • Qi Chen, Sihai Tang, Qing Yang, Song Fu
A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds.
Ranked #3 on
3D Object Detection
on OPV2V
no code implementations • WS 2019 • Hai Hu, Qi Chen, Larry Moss
This paper describes a working system which performs natural language inference using polarity-marked parse trees.
1 code implementation • 27 Mar 2019 • Yong Guo, Qi Chen, Jian Chen, Qingyao Wu, Qinfeng Shi, Mingkui Tan
To address this issue, we develop a novel GAN called Auto-Embedding Generative Adversarial Network (AEGAN), which simultaneously encodes the global structure features and captures the fine-grained details.
no code implementations • 3 Nov 2018 • Qiangguo Jin, Zhaopeng Meng, Tuan D. Pham, Qi Chen, Leyi Wei, Ran Su
Results show that more detailed vessels are extracted by DUNet and it exhibits state-of-the-art performance for retinal vessel segmentation with a global accuracy of 0. 9697/0. 9722/0. 9724 and AUC of 0. 9856/0. 9868/0. 9863 on DRIVE, STARE and CHASE_DB1 respectively.
Ranked #5 on
Retinal Vessel Segmentation
on STARE
no code implementations • EMNLP 2018 • Chen Shi, Qi Chen, Lei Sha, Sujian Li, Xu Sun, Houfeng Wang, Lintao Zhang
The lack of labeled data is one of the main challenges when building a task-oriented dialogue system.
no code implementations • 28 Sep 2018 • Zhiling Guo, Hiroaki Shengoku, Guangming Wu, Qi Chen, Wei Yuan, Xiaodan Shi, Xiaowei Shao, Yongwei Xu, Ryosuke Shibasaki
The results indicate the proposed method can serve as a viable tool for urban planning map semantic segmentation task with high accuracy and efficiency.
no code implementations • 19 Sep 2018 • Yong Guo, Qi Chen, Jian Chen, Junzhou Huang, Yanwu Xu, JieZhang Cao, Peilin Zhao, Mingkui Tan
However, most deep learning methods employ feed-forward architectures, and thus the dependencies between LR and HR images are not fully exploited, leading to limited learning performance.
no code implementations • 25 Jul 2018 • Qi Chen, Lei Wang, Yifan Wu, Guangming Wu, Zhiling Guo, Steven L. Waslander
In this paper, we present a new large-scale benchmark dataset termed Aerial Imagery for Roof Segmentation (AIRS).
no code implementations • 1 Apr 2018 • Qi Chen, Weichao Qiu, Yi Zhang, Lingxi Xie, Alan Yuille
But, this raises an important problem in active vision: given an {\bf infinite} data space, how to effectively sample a {\bf finite} subset to train a visual classifier?
no code implementations • 14 Dec 2016 • Yi Zhang, Weichao Qiu, Qi Chen, Xiaolin Hu, Alan Yuille
We generate a large synthetic image dataset with automatically computed hazardous regions and analyze algorithms on these regions.
no code implementations • 3 Jul 2016 • Le Dong, Zhiyu Lin, Yan Liang, Ling He, Ning Zhang, Qi Chen, Xiaochun Cao, Ebroul lzquierdo
The proposed ICP framework consists of two mechanisms, i. e. SICP (Static ICP) and DICP (Dynamic ICP).
no code implementations • 2 Sep 2014 • Qi Chen, Amanda Whitbrook, Uwe Aickelin, Chris Roadknight
In this paper, the Dempster-Shafer method is employed as the theoretical basis for creating data classification systems.