no code implementations • 11 Mar 2024 • Guosheng Zhao, XiaoFeng Wang, Zheng Zhu, Xinze Chen, Guan Huang, Xiaoyi Bao, Xingang Wang
DriveDreamer-2 is the first world model to generate customized driving videos, it can generate uncommon driving videos (e. g., vehicles abruptly cut in) in a user-friendly manner.
no code implementations • 18 Jan 2024 • XiaoFeng Wang, Zheng Zhu, Guan Huang, Boyuan Wang, Xinze Chen, Jiwen Lu
World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation.
no code implementations • 22 Dec 2023 • Ze Yu Zhao, Zheng Zhu, Guilin Li, Wenhan Wang, Bo wang
In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems.
1 code implementation • 1 Dec 2023 • Xianda Guo, Juntao Lu, Chenming Zhang, Yiqi Wang, Yiqun Duan, Tian Yang, Zheng Zhu, Long Chen
Based on OpenStereo, we conducted experiments and have achieved or surpassed the performance metrics reported in the original paper.
1 code implementation • 9 Nov 2023 • Licheng Wen, Xuemeng Yang, Daocheng Fu, XiaoFeng Wang, Pinlong Cai, Xin Li, Tao Ma, Yingxuan Li, Linran Xu, Dengke Shang, Zheng Zhu, Shaoyan Sun, Yeqi Bai, Xinyu Cai, Min Dou, Shuanglu Hu, Botian Shi, Yu Qiao
This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving.
1 code implementation • 23 Oct 2023 • Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Kaipeng Zhang, Wei Jiang, Yang You
Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones.
no code implementations • 18 Sep 2023 • XiaoFeng Wang, Zheng Zhu, Guan Huang, Xinze Chen, Jiagang Zhu, Jiwen Lu
The established world model holds immense potential for the generation of high-quality driving videos, and driving policies for safe maneuvering.
2 code implementations • 11 Sep 2023 • Chengkun Wang, Wenzhao Zheng, Zheng Zhu, Jie zhou, Jiwen Lu
This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images.
1 code implementation • 26 Aug 2023 • Jianqiang Xia, Dianxi Shi, Ke Song, Linna Song, Xiaolei Wang, Songchang Jin, Li Zhou, Yu Cheng, Lei Jin, Zheng Zhu, Jianan Li, Gang Wang, Junliang Xing, Jian Zhao
With this structure, the network can extract fusion features of the template and search region under the mutual interaction of modalities.
Ranked #1 on Rgb-T Tracking on GTOT
1 code implementation • 27 Jun 2023 • Xue-Feng Zhu, Tianyang Xu, Jian Zhao, Jia-Wei Liu, Kai Wang, Gang Wang, Jianan Li, Qiang Wang, Lei Jin, Zheng Zhu, Junliang Xing, Xiao-Jun Wu
Still, previous works have simplified such an anti-UAV task as a tracking problem, where the prior information of UAVs is always provided; such a scheme fails in real-world anti-UAV tasks (i. e. complex scenes, indeterminate-appear and -reappear UAVs, and real-time UAV surveillance).
no code implementations • 22 Jun 2023 • Bohan Li, Yasheng Sun, Jingxin Dong, Zheng Zhu, Jinming Liu, Xin Jin, Wenjun Zeng
Numerous studies have investigated the pivotal role of reliable 3D volume representation in scene perception tasks, such as multi-view stereo (MVS) and semantic scene completion (SSC).
no code implementations • 12 May 2023 • Jian Zhao, Jianan Li, Lei Jin, Jiaming Chu, Zhihao Zhang, Jun Wang, Jiangqiang Xia, Kai Wang, Yang Liu, Sadaf Gulshad, Jiaojiao Zhao, Tianyang Xu, XueFeng Zhu, Shihan Liu, Zheng Zhu, Guibo Zhu, Zechao Li, Zheng Wang, Baigui Sun, Yandong Guo, Shin ichi Satoh, Junliang Xing, Jane Shen Shengmei
Second, we set up two tracks for the first time, i. e., Anti-UAV Tracking and Anti-UAV Detection & Tracking.
1 code implementation • 10 May 2023 • Yingjie Tian, Yiqi Wang, Xianda Guo, Zheng Zhu, Long Chen
In recent years, soft prompt learning methods have been proposed to fine-tune large-scale vision-language pre-trained models for various downstream tasks.
1 code implementation • ICCV 2023 • Yunpeng Zhang, Zheng Zhu, Dalong Du
The vision-based perception for autonomous driving has undergone a transformation from the bird-eye-view (BEV) representations to the 3D semantic occupancy.
3D Semantic Occupancy Prediction 3D Semantic Scene Completion from a single RGB image +3
no code implementations • ICCV 2023 • Ming Wang, Xianda Guo, Beibei Lin, Tian Yang, Zheng Zhu, Lincheng Li, Shunli Zhang, Xin Yu
This is the first framework on gait recognition that is designed to focus on the extraction of dynamic features.
2 code implementations • ICCV 2023 • Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Jie zhou, Jiwen Lu
Towards a more comprehensive perception of a 3D scene, in this paper, we propose a SurroundOcc method to predict the 3D occupancy with multi-camera images.
1 code implementation • 15 Mar 2023 • Jiayu Zou, Zheng Zhu, Yun Ye, Xingang Wang
Diffusion models naturally have the ability to denoise noisy samples to the ideal data, which motivates us to utilize the diffusion model to get a better BEV representation.
no code implementations • 14 Mar 2023 • Xianda Guo, Wenjie Yuan, Yunpeng Zhang, Tian Yang, Chenming Zhang, Zheng Zhu, Long Chen
The former is achieved by the self-attention module within each view, while the latter is realized by the adjacent attention module, which computes the attention across multi-cameras to exchange the multi-scale representations across surround-view feature maps.
1 code implementation • 9 Mar 2023 • Yiqun Duan, Xianda Guo, Zheng Zhu
We propose DiffusionDepth, a new approach that reformulates monocular depth estimation as a denoising diffusion process.
2 code implementations • 8 Mar 2023 • Kai Wang, Jianyang Gu, Daquan Zhou, Zheng Zhu, Wei Jiang, Yang You
To the best of our knowledge, we are the first to achieve higher accuracy on complex architectures than simple ones, such as 75. 1\% with ResNet-18 and 72. 6\% with ConvNet-3 on ten images per class of CIFAR-10.
1 code implementation • ICCV 2023 • XiaoFeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang, Yi Wei, Xu Chi, Yun Ye, Dalong Du, Jiwen Lu, Xingang Wang
Towards a comprehensive benchmarking of surrounding perception algorithms, we propose OpenOccupancy, which is the first surrounding semantic occupancy perception benchmark.
2 code implementations • ICCV 2023 • Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Wei Jiang, Yang You
Although there are various matching objectives, currently the strategy for selecting original images is limited to naive random sampling.
1 code implementation • CVPR 2023 • Shuai Shen, Wenliang Zhao, Zibin Meng, Wanhua Li, Zheng Zhu, Jie zhou, Jiwen Lu
In this way, the proposed DiffTalk is capable of producing high-quality talking head videos in synchronization with the source audio, and more importantly, it can be naturally generalized across different identities without any further fine-tuning.
1 code implementation • 1 Jan 2023 • Boyu Zhang, Wenbo Xu, Zheng Zhu, Guan Huang
Specifically, it employs a neural representation to capture the scene distribution in the static background and a 6D-input NeRF to represent dynamic objects, respectively.
1 code implementation • CVPR 2023 • XiaoFeng Wang, Zheng Zhu, Yunpeng Zhang, Guan Huang, Yun Ye, Wenbo Xu, Ziwei Chen, Xingang Wang
To mitigate the problem, we propose the Autonomous-driving StreAming Perception (ASAP) benchmark, which is the first benchmark to evaluate the online performance of vision-centric perception in autonomous driving.
1 code implementation • ICCV 2023 • Han Xiao, Wenzhao Zheng, Zheng Zhu, Jie zhou, Jiwen Lu
Data mixing strategies (e. g., CutMix) have shown the ability to greatly improve the performance of convolutional neural networks (CNNs).
1 code implementation • ICCV 2023 • Chengkun Wang, Wenzhao Zheng, Zheng Zhu, Jie zhou, Jiwen Lu
The pretrain-finetune paradigm in modern computer vision facilitates the success of self-supervised learning, which tends to achieve better transferability than supervised learning.
1 code implementation • 22 Aug 2022 • Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu, Guan Huang, Jie zhou, Jiwen Lu
First, we extract multi-scale features and generate the perspective object proposals on each monocular image.
1 code implementation • 19 Aug 2022 • XiaoFeng Wang, Zheng Zhu, Guan Huang, Xu Chi, Yun Ye, Ziwei Chen, Xingang Wang
In contrast, multi-frame depth estimation methods improve the depth accuracy thanks to the success of Multi-View Stereo (MVS), which directly makes use of geometric constraints.
1 code implementation • 6 Aug 2022 • Chaoqiang Zhao, Youmin Zhang, Matteo Poggi, Fabio Tosi, Xianda Guo, Zheng Zhu, Guan Huang, Yang Tang, Stefano Mattoccia
Self-supervised monocular depth estimation is an attractive solution that does not require hard-to-source depth labels for training.
Ranked #1 on Monocular Depth Estimation on KITTI
1 code implementation • 24 Jul 2022 • Shuai Shen, Wanhua Li, Zheng Zhu, Yueqi Duan, Jie zhou, Jiwen Lu
Thus the facial radiance field can be flexibly adjusted to the new identity with few reference images.
1 code implementation • CVPR 2022 • Han Xiao, Ziwei Wang, Zheng Zhu, Jie zhou, Jiwen Lu
Differentiable architecture search (DARTS) acquires the optimal architectures by optimizing the architecture parameters with gradient descent, which significantly reduces the search cost.
1 code implementation • 6 Jun 2022 • Wanhua Li, Xiaoke Huang, Zheng Zhu, Yansong Tang, Xiu Li, Jie zhou, Jiwen Lu
In this paper, we propose to learn the rank concepts from the rich semantic CLIP latent space.
Ranked #1 on Few-shot Age Estimation on MORPH Album2
1 code implementation • 28 May 2022 • Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng, Lihua Xie, Yang You
Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain.
1 code implementation • 23 May 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Jiankang Deng, Xinchao Wang, Hakan Bilen, Yang You
Firstly, randomly masked face images are used to train the reconstruction module in FaceMAE.
1 code implementation • 19 May 2022 • Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng, JunJie Huang, Guan Huang, Jie zhou, Jiwen Lu
Specifically, BEVerse first performs shared feature extraction and lifting to generate 4D BEV representations from multi-timestamp and multi-view images.
Ranked #15 on Robust Camera Only 3D Object Detection on nuScenes-C
no code implementations • ICCV 2021 • Xianda Guo, Zheng Zhu, Tian Yang, Beibei Lin, JunJie Huang, Jiankang Deng, Guan Huang, Jie zhou, Jiwen Lu
To the best of our knowledge, this is the first large-scale dataset for gait recognition in the wild.
1 code implementation • 30 Apr 2022 • Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You
This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.
no code implementations • 21 Apr 2022 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Dalong Du, Jiwen Lu, Jie zhou
For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively.
1 code implementation • 15 Apr 2022 • XiaoFeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang, Xu Chi, Yijia He, Xingang Wang
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
1 code implementation • 11 Apr 2022 • Jiayu Zou, Junrui Xiao, Zheng Zhu, JunJie Huang, Guan Huang, Dalong Du, Xingang Wang
In order to reap the benefits and avoid the drawbacks of CBFT and CFFT, we propose a novel framework with a Hybrid Feature Transformation module (HFT).
1 code implementation • 7 Apr 2022 • Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Yongming Rao, Guan Huang, Jiwen Lu, Jie zhou
In this paper, we propose a SurroundDepth method to incorporate the information from multiple surrounding views to predict depth maps across cameras.
1 code implementation • CVPR 2022 • Qingping Zheng, Jiankang Deng, Zheng Zhu, Ying Li, Stefanos Zafeiriou
Specifically, DML-CSR designs a multi-task model which comprises face parsing, binary edge, and category edge detection.
Ranked #1 on Face Parsing on Helen
1 code implementation • 8 Mar 2022 • Ming Wang, Beibei Lin, Xianda Guo, Lincheng Li, Zheng Zhu, Jiande Sun, Shunli Zhang, Xin Yu
ECM consists of the Spatial-Temporal feature extractor (ST), the Frame-Level feature extractor (FL) and SPB, and has two obvious advantages: First, each branch focuses on a specific representation, which can be used to improve the robustness of the network.
2 code implementations • CVPR 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.
1 code implementation • CVPR 2022 • Xiangyu Peng, Kai Wang, Zheng Zhu, Mang Wang, Yang You
For high performance Siamese representation learning, one of the keys is to design good contrastive pairs.
no code implementations • CVPR 2022 • Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu, Guan Huang, Dalong Du, Jie zhou, Jiwen Lu
In this paper, we propose a general method to learn appropriate embeddings for dimension estimation in monocular 3D object detection.
2 code implementations • 22 Dec 2021 • JunJie Huang, Guan Huang, Zheng Zhu, Yun Ye, Dalong Du
As a fast version, BEVDet-Tiny scores 31. 2% mAP and 39. 2% NDS on the nuScenes val set.
Ranked #20 on Robust Camera Only 3D Object Detection on nuScenes-C
1 code implementation • CVPR 2022 • Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie zhou, Jiwen Lu
In this work, we present a new framework for dense prediction by implicitly and explicitly leveraging the pre-trained knowledge from CLIP.
no code implementations • 10 Sep 2021 • Yunze Chen, JunJie Huang, Jiagang Zhu, Zheng Zhu, Tian Yang, Guan Huang, Dalong Du
The current research on this problem mainly focuses on designing an efficient Fully-connected layer (FC) to reduce GPU memory consumption caused by a large number of identities.
1 code implementation • 18 Aug 2021 • Jiankang Deng, Jia Guo, Xiang An, Zheng Zhu, Stefanos Zafeiriou
In this workshop, we organize Masked Face Recognition (MFR) challenge and focus on bench-marking deep face recognition methods under the existence of facial masks.
no code implementations • 16 Aug 2021 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jia Guo, Jiwen Lu, Dalong Du, Jie zhou
There are second phase of the challenge till October 1, 2021 and on-going leaderboard.
4 code implementations • NeurIPS 2021 • Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie zhou
Recent advances in self-attention and pure multi-layer perceptrons (MLP) models for vision have shown great potential in achieving promising performance with fewer inductive biases.
Ranked #9 on Image Classification on Stanford Cars (using extra training data)
1 code implementation • CVPR 2021 • Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou
To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.
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)
no code implementations • 6 Apr 2021 • Jiabin Zhang, Zheng Zhu, Jiwen Lu, JunJie Huang, Guan Huang, Jie zhou
To make a better trade-off between accuracy and efficiency, we propose a novel multi-person pose estimation framework, SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation (SIMPLE).
1 code implementation • 24 Mar 2021 • Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou
To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.
no code implementations • CVPR 2021 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jiwen Lu, Dalong Du, Jie zhou
In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training data, as well as an elaborately designed time-constrained evaluation protocol.
Ranked #1 on Face Verification on IJB-C (training dataset metric)
no code implementations • 11 Nov 2020 • Jintao Ke, Siyuan Feng, Zheng Zhu, Hai Yang, Jieping Ye
To address this issue, we propose a deep multi-task multi-graph learning approach, which combines two components: (1) multiple multi-graph convolutional (MGC) networks for predicting demands for different service modes, and (2) multi-task learning modules that enable knowledge sharing across multiple MGC networks.
no code implementations • 11 Sep 2020 • Weihua Liu, Xiabi Liua, Xiongbiao Luo, Murong Wang, Guanghui Han, Xinming Zhao, Zheng Zhu
In the first stage, the feature-extraction module is embedded into a classifier network that is trained on a large data set of GGO and non-GGO patches, which are generated by performing data augmentation from a small number of annotated CT scans.
2 code implementations • 17 Aug 2020 • Junjie Huang, Zheng Zhu, Guan Huang, Dalong Du
As AID successfully pushes the performance boundary of human pose estimation problem by considerable margin and sets a new state-of-the-art, we hope AID to be a regular configuration for training human pose estimators.
Ranked #1 on Multi-Person Pose Estimation on COCO minival
3 code implementations • CVPR 2020 • Junjie Huang, Zheng Zhu, Feng Guo, Guan Huang, Dalong Du
Specifically, by investigating the standard data processing in state-of-the-art approaches mainly including coordinate system transformation and keypoint format transformation (i. e., encoding and decoding), we find that the results obtained by common flipping strategy are unaligned with the original ones in inference.
Ranked #14 on Pose Estimation on COCO test-dev
1 code implementation • 17 Oct 2019 • Jintao Ke, Xiaoran Qin, Hai Yang, Zhengfei Zheng, Zheng Zhu, Jieping Ye
To overcome this challenge, we propose the Spatio-Temporal Encoder-Decoder Residual Multi-Graph Convolutional network (ST-ED-RMGC), a novel deep learning model for predicting ride-sourcing demand of various OD pairs.
no code implementations • 14 Oct 2019 • Junjie Huang, Zheng Zhu, Guan Huang
Human pose estimation are of importance for visual understanding tasks such as action recognition and human-computer interaction.
no code implementations • 24 Sep 2019 • Hongxuan Ma, Wei Zou, Zheng Zhu, Siyang Sun, Zhaobing Kang
In the field of navigation and visual servo, it is common to calculate relative pose by feature points on markers, so keeping markers in camera's view is an important problem.
1 code implementation • 19 Sep 2019 • Zhaobing Kang, Wei Zou, Zheng Zhu, Chi Zhang, Hongxuan Ma
This paper presents a generic 6DOF camera pose estimation method, which can be used for both the pinhole camera and the fish-eye camera.
no code implementations • 13 Sep 2019 • Zheng Zhu, Hongxuan Ma, Wei Zou
Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications.
no code implementations • 26 Aug 2019 • Zheng Zhu, Wei Zou, Guan Huang, Dalong Du, Chang Huang
In this paper, we propose an end-to-end framework to learn the convolutional features and perform the tracking process simultaneously, namely, a unified convolutional tracker (UCT).
no code implementations • 24 Aug 2019 • Zhaobing Kang, Wei Zou, Zheng Zhu
Firstly, the relationship between the camera pose estimation error and bias values of map points is derived based on the optimized function in VSLAM.
no code implementations • 15 Aug 2019 • Jiabin Zhang, Zheng Zhu, Wei Zou, Peng Li, Yanwei Li, Hu Su, Guan Huang
Given the results of MTN, we adopt an occlusion-aware Re-ID feature strategy in the pose tracking module, where pose information is utilized to infer the occlusion state to make better use of Re-ID feature.
no code implementations • 4 Jun 2019 • Rui Zhang, Zheng Zhu, Peng Li, Rui Wu, Chaoxu Guo, Guan Huang, Hailun Xia
Human pose estimation has witnessed a significant advance thanks to the development of deep learning.
no code implementations • 4 Jun 2019 • Peng Li, Jiabin Zhang, Zheng Zhu, Yanwei Li, Lu Jiang, Guan Huang
Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajectories from videos captured by a set of cameras.
no code implementations • 14 Dec 2018 • Jiagang Zhu, Wei Zou, Liang Xu, Yiming Hu, Zheng Zhu, Manyu Chang, Jun-Jie Huang, Guan Huang, Dalong Du
On NTU RGB-D, Action Machine achieves the state-of-the-art performance with top-1 accuracies of 97. 2% and 94. 3% on cross-view and cross-subject respectively.
Ranked #1 on Action Recognition on UTD-MHAD
no code implementations • 11 Dec 2018 • Yanwei Li, Xingang Wang, Shilei Zhang, Lingxi Xie, Wenqi Wu, Hongyuan Yu, Zheng Zhu
Facial expression recognition is a challenging task, arguably because of large intra-class variations and high inter-class similarities.
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • CVPR 2019 • Yanwei Li, Xinze Chen, Zheng Zhu, Lingxi Xie, Guan Huang, Dalong Du, Xingang Wang
This paper studies panoptic segmentation, a recently proposed task which segments foreground (FG) objects at the instance level as well as background (BG) contents at the semantic level.
Ranked #24 on Panoptic Segmentation on COCO test-dev
1 code implementation • 26 Nov 2018 • Shuai Bai, Zhiqun He, Ting-Bing Xu, Zheng Zhu, Yuan Dong, Hongliang Bai
For visual tracking, most of the traditional correlation filters (CF) based methods suffer from the bottleneck of feature redundancy and lack of motion information.
no code implementations • 18 Nov 2018 • Junjie Huang, Wei Zou, Zheng Zhu, Jiagang Zhu
Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource.
Motion Detection Motion Detection In Non-Stationary Scenes +1
no code implementations • 18 Nov 2018 • Junjie Huang, Wei Zou, Zheng Zhu, Jiagang Zhu
Obtained by moving object detection, the foreground mask result is unshaped and can not be directly used in most subsequent processes.
1 code implementation • ECCV 2018 • Zheng Zhu, Qiang Wang, Bo Li, Wei Wu, Junjie Yan, Weiming Hu
During the off-line training phase, an effective sampling strategy is introduced to control this distribution and make the model focus on the semantic distractors.
Ranked #11 on Visual Object Tracking on VOT2017/18
no code implementations • 13 Jul 2018 • Junjie Huang, Wei Zou, Jiagang Zhu, Zheng Zhu
Real-time moving object detection in unconstrained scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource.
5 code implementations • CVPR 2018 • Bo Li, Junjie Yan, Wei Wu, Zheng Zhu, Xiaolin Hu
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
Ranked #7 on Visual Object Tracking on VOT2017/18
1 code implementation • 11 Nov 2017 • Jiagang Zhu, Wei Zou, Zheng Zhu
From the frame/clip-level feature learning to the video-level representation building, deep learning methods in action recognition have developed rapidly in recent years.
no code implementations • 10 Nov 2017 • Zheng Zhu, Guan Huang, Wei Zou, Dalong Du, Chang Huang
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks.
no code implementations • CVPR 2018 • Zheng Zhu, Wei Wu, Wei Zou, Junjie Yan
Discriminative correlation filters (DCF) with deep convolutional features have achieved favorable performance in recent tracking benchmarks.
1 code implementation • 12 Sep 2017 • Jiagang Zhu, Wei Zou, Zheng Zhu
For the two-stream style methods in action recognition, fusing the two streams' predictions is always by the weighted averaging scheme.
no code implementations • 27 May 2017 • Oleg Sofrygin, Zheng Zhu, Julie A Schmittdiel, Alyce S. Adams, Richard W. Grant, Mark J. Van Der Laan, Romain Neugebauer
Electronic health records (EHR) data provide a cost and time-effective opportunity to conduct cohort studies of the effects of multiple time-point interventions in the diverse patient population found in real-world clinical settings.
no code implementations • 17 Aug 2016 • Roberto Santana, Zheng Zhu, Helmut G. Katzgraber
In this paper we investigate for the first time the use of Evolutionary Algorithms (EAs) on Ising spin glass instances defined on the Chimera topology.