Search Results for author: Zheng Qin

Found 29 papers, 13 papers with code

MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking

no code implementations18 Mar 2023 Zheng Qin, Sanping Zhou, Le Wang, Jinghai Duan, Gang Hua, Wei Tang

For dense crowds, we design a novel Interaction Module to learn interaction-aware motions from short-term trajectories, which can estimate the complex movement of each target.

motion prediction Multi-Object Tracking

Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration

1 code implementation17 Mar 2023 Zheng Qin, Hao Yu, Changjian Wang, Yuxing Peng, Kai Xu

We first design a local spatial consistency measure over the deformation graph of the point cloud, which evaluates the spatial compatibility only between the correspondences in the vicinity of a graph node.

Point Cloud Registration

Learning Accurate Template Matching with Differentiable Coarse-to-Fine Correspondence Refinement

1 code implementation15 Mar 2023 Zhirui Gao, Renjiao Yi, Zheng Qin, Yunfan Ye, Chenyang Zhu, Kai Xu

To tackle the challenges, we propose an accurate template matching method based on differentiable coarse-to-fine correspondence refinement.

Robotic Grasping Template Matching

Rotation-Invariant Transformer for Point Cloud Matching

1 code implementation14 Mar 2023 Hao Yu, Zheng Qin, Ji Hou, Mahdi Saleh, Dongsheng Li, Benjamin Busam, Slobodan Ilic

To this end, we introduce RoITr, a Rotation-Invariant Transformer to cope with the pose variations in the point cloud matching task.

Data Augmentation

DeepfakeMAE: Facial Part Consistency Aware Masked Autoencoder for Deepfake Video Detection

no code implementations3 Mar 2023 Juan Hu, Xin Liao, Difei Gao, Satoshi Tsutsui, Zheng Qin, Mike Zheng Shou

Furthermore, to maximize the discrepancy between real and fake videos, we propose a novel model with dual networks that utilize the pretrained encoder and decoder, respectively.

DeepFake Detection Face Swapping

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration

no code implementations27 Sep 2022 Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic

More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.

Point Cloud Registration

Unsupervised Voice-Face Representation Learning by Cross-Modal Prototype Contrast

1 code implementation28 Apr 2022 Boqing Zhu, Kele Xu, Changjian Wang, Zheng Qin, Tao Sun, Huaimin Wang, Yuxing Peng

We present an approach to learn voice-face representations from the talking face videos, without any identity labels.

Association Contrastive Learning +1

Multi-Modal Relational Graph for Cross-Modal Video Moment Retrieval

no code implementations CVPR 2021 Yawen Zeng, Da Cao, Xiaochi Wei, Meng Liu, Zhou Zhao, Zheng Qin

Toward this end, we contribute a multi-modal relational graph to capture the interactions among objects from the visual and textual content to identify the differences among similar video moment candidates.

Cross-Modal Retrieval Graph Matching +2

Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence

1 code implementation26 Oct 2020 Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R. Kulkarni, Dawn Song

Log-based cyber threat hunting has emerged as an important solution to counter sophisticated attacks.

Optimising Stochastic Routing for Taxi Fleets with Model Enhanced Reinforcement Learning

no code implementations22 Oct 2020 Shen Ren, Qianxiao Li, Liye Zhang, Zheng Qin, Bo Yang

The future of mobility-as-a-Service (Maas)should embrace an integrated system of ride-hailing, street-hailing and ride-sharing with optimised intelligent vehicle routing in response to a real-time, stochastic demand pattern.

reinforcement-learning Reinforcement Learning (RL)

Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation

1 code implementation28 Jun 2020 Wenhui Yu, Xiao Lin, Junfeng Ge, Wenwu Ou, Zheng Qin

This causes two difficulties in designing effective algorithms: first, the majority of users only have a few interactions with the system and there is no enough data for learning; second, there are no negative samples in the implicit feedbacks and it is a common practice to perform negative sampling to generate negative samples.

Collaborative Filtering Domain Adaptation +1

Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters

2 code implementations ICML 2020 Wenhui Yu, Zheng Qin

\textbf{G}raph \textbf{C}onvolutional \textbf{N}etwork (\textbf{GCN}) is widely used in graph data learning tasks such as recommendation.


Sampler Design for Implicit Feedback Data by Noisy-label Robust Learning

1 code implementation28 Jun 2020 Wenhui Yu, Zheng Qin

We predict users' preferences with the model and learn it by maximizing likelihood of observed data labels, i. e., a user prefers her positive samples and has no interests in her unvoted samples.

ThunderNet: Towards Real-Time Generic Object Detection on Mobile Devices

no code implementations ICCV 2019 Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, Jian Sun

In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.

object-detection Object Detection

Visually-aware Recommendation with Aesthetic Features

no code implementations2 May 2019 Wenhui Yu, Xiangnan He, Jian Pei, Xu Chen, Li Xiong, Jinfei Liu, Zheng Qin

While recent developments on visually-aware recommender systems have taken the product image into account, none of them has considered the aesthetic aspect.

Decision Making Recommendation Systems +1

Spectrum-enhanced Pairwise Learning to Rank

no code implementations2 May 2019 Wenhui Yu, Zheng Qin

However, there are some demerits of side information: (1) the extra data is not always available in all recommendation tasks; (2) it is only for items, there is seldom high-level feature describing users.

Learning-To-Rank Recommendation Systems

ThunderNet: Towards Real-time Generic Object Detection

4 code implementations28 Mar 2019 Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, Jian Sun

In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.

object-detection Object Detection

Aesthetic-based Clothing Recommendation

no code implementations16 Sep 2018 Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, Zheng Qin

Considering that the aesthetic preference varies significantly from user to user and by time, we then propose a new tensor factorization model to incorporate the aesthetic features in a personalized manner.

Recommendation Systems

Bridge Video and Text with Cascade Syntactic Structure

no code implementations COLING 2018 Guolong Wang, Zheng Qin, Kaiping Xu, Kai Huang, Shuxiong Ye

We present a video captioning approach that encodes features by progressively completing syntactic structure (LSTM-CSS).

Region Proposal Video Captioning +1

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

no code implementations10 Apr 2018 Hao Yu, Zhaoning Zhang, Zheng Qin, Hao Wu, Dongsheng Li, Jun Zhao, Xicheng Lu

LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples.

Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions

3 code implementations27 Mar 2018 Zheng Qin, Zhaoning Zhang, Dongsheng Li, Yiming Zhang, Yuxing Peng

Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds.

Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications

2 code implementations24 Mar 2018 Zheng Qin, Zhaoning Zhang, Shiqing Zhang, Hao Yu, Yuxing Peng

Compact neural networks are inclined to exploit "sparsely-connected" convolutions such as depthwise convolution and group convolution for employment in mobile applications.

FD-MobileNet: Improved MobileNet with a Fast Downsampling Strategy

2 code implementations11 Feb 2018 Zheng Qin, Zhaoning Zhang, Xiaotao Chen, Yuxing Peng

Experiments on ILSVRC 2012 and PASCAL VOC 2007 datasets demonstrate that FD-MobileNet consistently outperforms MobileNet and achieves comparable results with ShuffleNet under different computational budgets, for instance, surpassing MobileNet by 5. 5% on the ILSVRC 2012 top-1 accuracy and 3. 6% on the VOC 2007 mAP under a complexity of 12 MFLOPs.

Visually Explainable Recommendation

no code implementations31 Jan 2018 Xu Chen, Yongfeng Zhang, Hongteng Xu, Yixin Cao, Zheng Qin, Hongyuan Zha

By this, we can not only provide recommendation results to the users, but also tell the users why an item is recommended by providing intuitive visual highlights in a personalized manner.

Explainable Recommendation Recommendation Systems

Transfer Hashing with Privileged Information

no code implementations13 May 2016 Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh

Specifically, we extend the standard learning to hash method, Iterative Quantization (ITQ), in a transfer learning manner, namely ITQ+.

Quantization Transfer Learning

Simple and Efficient Learning using Privileged Information

no code implementations6 Apr 2016 Xinxing Xu, Joey Tianyi Zhou, IvorW. Tsang, Zheng Qin, Rick Siow Mong Goh, Yong liu

The Support Vector Machine using Privileged Information (SVM+) has been proposed to train a classifier to utilize the additional privileged information that is only available in the training phase but not available in the test phase.

Image Categorization

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