no code implementations • 6 Nov 2023 • Xiao Tan, Antonis Papachristodoulou, Dimos V. Dimarogonas
This paper proposes a (control) barrier function synthesis and safety verification scheme for interconnected nonlinear systems based on assume-guarantee contracts (AGC) and sum-of-squares (SOS) techniques.
no code implementations • ICCV 2023 • Xiang Guo, Jiadai Sun, Yuchao Dai, GuanYing Chen, Xiaoqing Ye, Xiao Tan, Errui Ding, Yumeng Zhang, Jingdong Wang
This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping.
1 code implementation • 17 Sep 2023 • Pian Yu, Xiao Tan, Dimos V. Dimarogonas
In this work, we propose an efficient continuous-time control synthesis framework for nonlinear systems under nested STL specifications.
no code implementations • 18 Jul 2023 • Chaofeng Chen, Wei Liu, Xiao Tan, Kwan-Yee K. Wong
Experiments show that SCG achieves competitive performance on public benchmarks and superior results on photos in the wild.
3 code implementations • CVPR 2023 • Jiacheng Zhang, Xiangru Lin, Wei zhang, Kuo Wang, Xiao Tan, Junyu Han, Errui Ding, Jingdong Wang, Guanbin Li
Specifically, we propose a Stage-wise Hybrid Matching strategy that combines the one-to-many assignment and one-to-one assignment strategies to improve the training efficiency of the first stage and thus provide high-quality pseudo labels for the training of the second stage.
no code implementations • 6 Jul 2023 • Jincheng Lu, Xipeng Yang, Jin Ye, Yifu Zhang, Zhikang Zou, Wei zhang, Xiao Tan
Targets in urban traffic scenes often undergo occlusion, illumination changes, and perspective changes, making it difficult to associate targets across different cameras accurately.
1 code implementation • 12 May 2023 • Zhe Liu, Xiaoqing Ye, Zhikang Zou, Xinwei He, Xiao Tan, Errui Ding, Jingdong Wang, Xiang Bai
Extensive experiments on the nuScenes dataset demonstrate that our method is much more stable in dealing with challenging cases such as asynchronous sensors, misaligned sensor placement, and degenerated camera images than existing fusion methods.
Ranked #47 on
3D Object Detection
on nuScenes
no code implementations • 9 May 2023 • Adrian Wiltz, Xiao Tan, Dimos V. Dimarogonas
We show that, based on ideas similar to the Hamilton-Jacobi reachability analysis, the knowledge on the subset of a control-invariant set allows us to obtain a time-invariant CBF for the time-invariant dynamics under consideration.
1 code implementation • CVPR 2023 • Chang Liu, Weiming Zhang, Xiangru Lin, Wei zhang, Xiao Tan, Junyu Han, Xiaomao Li, Errui Ding, Jingdong Wang
It employs a "divide-and-conquer" strategy and separately exploits positives for the classification and localization task, which is more robust to the assignment ambiguity.
Ranked #1 on
Semi-Supervised Object Detection
on COCO 10% labeled data
(detector metric)
no code implementations • 27 Mar 2023 • Yifu Zhang, Xinggang Wang, Xiaoqing Ye, Wei zhang, Jincheng Lu, Xiao Tan, Errui Ding, Peize Sun, Jingdong Wang
We propose a hierarchical data association strategy to mine the true objects in low-score detection boxes, which alleviates the problems of object missing and fragmented trajectories.
2 code implementations • CVPR 2023 • Kaixin Xiong, Shi Gong, Xiaoqing Ye, Xiao Tan, Ji Wan, Errui Ding, Jingdong Wang, Xiang Bai
In this paper, we address the problem of detecting 3D objects from multi-view images.
Ranked #7 on
3D Object Detection
on nuScenes Camera Only
no code implementations • 9 Mar 2023 • Feng He, Qi Wang, Zhifan Feng, Wenbin Jiang, Yajuan Lv, Yong Zhu, Xiao Tan
While most video retrieval methods overlook that phenomenon, we propose an adaptive margin changed with the distance between positive and negative pairs to solve the aforementioned issue.
no code implementations • 4 Jan 2023 • Zhe Liu, Xiaoqing Ye, Xiao Tan, Errui Ding, Xiang Bai
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors from the superior LiDAR model at the response level, which is usually overlooked in 3D object detection distillation.
no code implementations • ICCV 2023 • Shuo Li, Yue He, Weiming Zhang , Wei zhang, Xiao Tan, Junyu Han, Errui Ding, Jingdong Wang
Current state-of-the-art semi-supervised semantic segmentation (SSSS) methods typically adopt pseudo labeling and consistency regularization between multiple learners with different perturbations.
1 code implementation • ICCV 2023 • Jiaming Li, Xiangru Lin, Wei zhang, Xiao Tan, YingYing Li, Junyu Han, Errui Ding, Jingdong Wang, Guanbin Li
To tackle the confirmation bias from incorrect pseudo labels of minority classes, the class-rebalancing sampling module resamples unlabeled data following the guidance of the gradient-based reweighting module.
no code implementations • ICCV 2023 • Dingyuan Zhang, Dingkang Liang, Zhikang Zou, Jingyu Li, Xiaoqing Ye, Zhe Liu, Xiao Tan, Xiang Bai
Advanced 3D object detection methods usually rely on large-scale, elaborately labeled datasets to achieve good performance.
no code implementations • CVPR 2023 • Ruihang Chu, Zhengzhe Liu, Xiaoqing Ye, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, Jiaya Jia
The key of Cart is to utilize the prediction of object structures to connect visual observations with user commands for effective manipulations.
no code implementations • 11 Oct 2022 • Yue He, Minyue Jiang, Xiaoqing Ye, Liang Du, Zhikang Zou, Wei zhang, Xiao Tan, Errui Ding
In this paper, we target at finding an enhanced feature space where the lane features are distinctive while maintaining a similar distribution of lanes in the wild.
1 code implementation • 8 Oct 2022 • Peizhe Jiang, Wei Yang, Xiaoqing Ye, Xiao Tan, Meng Wu
Monocular depth estimation (MDE) in the self-supervised scenario has emerged as a promising method as it refrains from the requirement of ground truth depth.
7 code implementations • 5 Oct 2022 • Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
no code implementations • 28 Sep 2022 • Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi
3D scenes are dominated by a large number of background points, which is redundant for the detection task that mainly needs to focus on foreground objects.
no code implementations • 6 Sep 2022 • Xiao Tan, Dimos V. Dimarogonas
State and input constraints are ubiquitous in control system design.
no code implementations • 24 Aug 2022 • Liang Du, Xiaoqing Ye, Xiao Tan, Edward Johns, Bo Chen, Errui Ding, xiangyang xue, Jianfeng Feng
A feasible method is investigated to construct conceptual scenes without external datasets.
no code implementations • 12 Jul 2022 • Bo Ju, Zhikang Zou, Xiaoqing Ye, Minyue Jiang, Xiao Tan, Errui Ding, Jingdong Wang
In this work, we propose a novel semantic passing framework, named SPNet, to boost the performance of existing lidar-based 3D detection models with the guidance of rich context painting, with no extra computation cost during inference.
no code implementations • 15 Jun 2022 • Xiang Guo, GuanYing Chen, Yuchao Dai, Xiaoqing Ye, Jiadai Sun, Xiao Tan, Errui Ding
The second module contains a density and a color grid to model the geometry and density of the scene.
1 code implementation • 25 Apr 2022 • Xiao Tan, Jingbo Gao, Ruolin Li
As deep learning applications, especially programs of computer vision, are increasingly deployed in our lives, we have to think more urgently about the security of these applications. One effective way to improve the security of deep learning models is to perform adversarial training, which allows the model to be compatible with samples that are deliberately created for use in attacking the model. Based on this, we propose a simple architecture to build a model with a certain degree of robustness, which improves the robustness of the trained network by adding an adversarial sample detection network for cooperative training.
no code implementations • 16 Apr 2022 • Shi Gong, Xiaoqing Ye, Xiao Tan, Jingdong Wang, Errui Ding, Yu Zhou, Xiang Bai
Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability.
1 code implementation • CVPR 2022 • Lin Chen, Huaian Chen, Zhixiang Wei, Xin Jin, Xiao Tan, Yi Jin, Enhong Chen
Such NWD can be coupled with the classifier to serve as a discriminator satisfying the K-Lipschitz constraint without the requirements of additional weight clipping or gradient penalty strategy.
Ranked #1 on
Domain Adaptation
on ImageCLEF-DA
no code implementations • 25 Mar 2022 • Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding
On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.
no code implementations • CVPR 2022 • Ruihang Chu, Xiaoqing Ye, Zhengzhe Liu, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, Jiaya Jia
We explore the way to alleviate the label-hungry problem in a semi-supervised setting for 3D instance segmentation.
no code implementations • CVPR 2022 • Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding
On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.
no code implementations • ICCV 2021 • Zhikang Zou, Xiaoqing Ye, Liang Du, Xianhui Cheng, Xiao Tan, Li Zhang, Jianfeng Feng, xiangyang xue, Errui Ding
Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory.
1 code implementation • 3 Dec 2021 • Zheyuan Zhou, Liang Du, Xiaoqing Ye, Zhikang Zou, Xiao Tan, Li Zhang, xiangyang xue, Jianfeng Feng
Monocular 3D object detection aims to predict the object location, dimension and orientation in 3D space alongside the object category given only a monocular image.
no code implementations • 9 Aug 2021 • Jie Wu, Wei zhang, Guanbin Li, Wenhao Wu, Xiao Tan, YingYing Li, Errui Ding, Liang Lin
In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video.
1 code implementation • 25 May 2021 • Wenhao Wu, Yuxiang Zhao, Yanwu Xu, Xiao Tan, Dongliang He, Zhikang Zou, Jin Ye, YingYing Li, Mingde Yao, ZiChao Dong, Yifeng Shi
Long-range and short-range temporal modeling are two complementary and crucial aspects of video recognition.
Ranked #5 on
Action Recognition
on ActivityNet
1 code implementation • 9 May 2021 • Yuxiang Zhao, Wenhao Wu, Yue He, YingYing Li, Xiao Tan, Shifeng Chen
In this paper, we propose a straightforward and efficient framework that includes pre-processing, a dynamic track module, and post-processing.
no code implementations • 30 Apr 2021 • Xiao Tan, Dimos V. Dimarogonas
In this paper, we analyze the system behavior for general nonlinear control-affine systems when a control barrier function-induced quadratic program-based controller is employed for feedback.
no code implementations • 31 Mar 2021 • Xiao Tan, Wenceslao Shaw Cortez, Dimos V. Dimarogonas
Furthermore, the proposed formulation accounts for "performance-critical" control: it guarantees that a subset of the forward invariant set will admit any existing, bounded control law, while still ensuring forward invariance of the set.
no code implementations • ICCV 2021 • Zhi Chen, Xiaoqing Ye, Wei Yang, Zhenbo Xu, Xiao Tan, Zhikang Zou, Errui Ding, Xinming Zhang, Liusheng Huang
Second, we introduce an occlusion-aware distillation (OA Distillation) module, which leverages the predicted depths from StereoNet in non-occluded regions to train our monocular depth estimation network named SingleNet.
1 code implementation • 14 Dec 2020 • Xuanmeng Zhang, Minyue Jiang, Zhedong Zheng, Xiao Tan, Errui Ding, Yi Yang
We argue that the first phase equals building the k-nearest neighbor graph, while the second phase can be viewed as spreading the message within the graph.
Ranked #1 on
Image Retrieval
on Oxford5k
no code implementations • 25 Oct 2020 • Mingyang Qian, Yi Fu, Xiao Tan, YingYing Li, Jinqing Qi, Huchuan Lu, Shilei Wen, Errui Ding
Video segmentation approaches are of great importance for numerous vision tasks especially in video manipulation for entertainment.
1 code implementation • NeurIPS 2020 • Di Hu, Rui Qian, Minyue Jiang, Xiao Tan, Shilei Wen, Errui Ding, Weiyao Lin, Dejing Dou
First, we propose to learn robust object representations by aggregating the candidate sound localization results in the single source scenes.
1 code implementation • 18 Sep 2020 • Chaofeng Chen, Xiao Tan, Kwan-Yee K. Wong
We utilize a fully convolutional neural network (FCNN) to create the content image, and propose a style transfer approach to introduce textures and shadings based on a newly proposed pyramid column feature.
1 code implementation • ECCV 2020 • Zhenbo Xu, Wei zhang, Xiao Tan, Wei Yang, Huan Huang, Shilei Wen, Errui Ding, Liusheng Huang
The resulting online MOTS framework, named PointTrack, surpasses all the state-of-the-art methods including 3D tracking methods by large margins (5. 4% higher MOTSA and 18 times faster over MOTSFusion) with the near real-time speed (22 FPS).
Multi-Object Tracking
Multi-Object Tracking and Segmentation
+1
1 code implementation • 3 Jul 2020 • Zhenbo Xu, Wei zhang, Xiao Tan, Wei Yang, Xiangbo Su, Yuchen Yuan, Hongwu Zhang, Shilei Wen, Errui Ding, Liusheng Huang
In this work, we present PointTrack++, an effective on-line framework for MOTS, which remarkably extends our recently proposed PointTrack framework.
no code implementations • CVPR 2020 • Liang Du, Xiaoqing Ye, Xiao Tan, Jianfeng Feng, Zhenbo Xu, Errui Ding, Shilei Wen
Object detection from 3D point clouds remains a challenging task, though recent studies pushed the envelope with the deep learning techniques.
1 code implementation • 1 Mar 2020 • Zhenbo Xu, Wei zhang, Xiaoqing Ye, Xiao Tan, Wei Yang, Shilei Wen, Errui Ding, Ajin Meng, Liusheng Huang
The pipeline of ZoomNet begins with an ordinary 2D object detection model which is used to obtain pairs of left-right bounding boxes.
no code implementations • 9 Feb 2020 • Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Yi Yang, Shilei Wen
In a nutshell, we treat input frames and network depth of the computational graph as a 2-dimensional grid, and several checkpoints are placed on this grid in advance with a prediction module.
1 code implementation • ICCV 2019 • Zhaoyi Yan, Yuchen Yuan, WangMeng Zuo, Xiao Tan, Yezhen Wang, Shilei Wen, Errui Ding
In this paper, we propose a novel perspective-guided convolution (PGC) for convolutional neural network (CNN) based crowd counting (i. e. PGCNet), which aims to overcome the dramatic intra-scene scale variations of people due to the perspective effect.
1 code implementation • ICCV 2019 • Xiangyun Zhao, Yi Yang, Feng Zhou, Xiao Tan, Yuchen Yuan, Yingze Bao, Ying Wu
Although great progress has been made to apply object-level recognition, recognizing the attributes of parts remains less applicable since the training data for part attributes recognition is usually scarce especially for internet-scale applications.
no code implementations • ICCV 2019 • Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Shilei Wen
Video Recognition has drawn great research interest and great progress has been made.
Ranked #6 on
Action Recognition
on ActivityNet
1 code implementation • 12 Dec 2018 • Chaofeng Chen, Wei Liu, Xiao Tan, Kwan-Yee K. Wong
Instead of supervising the network with ground truth sketches, we first perform patch matching in feature space between the input photo and photos in a small reference set of photo-sketch pairs.
Ranked #1 on
Face Sketch Synthesis
on CUHK
no code implementations • ECCV 2018 • Chen Zhu, Xiao Tan, Feng Zhou, Xiao Liu, Kaiyu Yue, Errui Ding, Yi Ma
Specifically, it firstly summarizes the video by weight-summing all feature vectors in the feature maps of selected frames with a spatio-temporal soft attention, and then predicts which channels to suppress or to enhance according to this summary with a learned non-linear transform.
Ranked #11 on
Action Recognition
on ActivityNet
2 code implementations • 19 Oct 2018 • Yaming Wang, Xiao Tan, Yi Yang, Ziyu Li, Xiao Liu, Feng Zhou, Larry S. Davis
Existing 3D pose datasets of object categories are limited to generic object types and lack of fine-grained information.
2 code implementations • 12 Jun 2018 • Yaming Wang, Xiao Tan, Yi Yang, Xiao Liu, Errui Ding, Feng Zhou, Larry S. Davis
The new dataset is available at www. umiacs. umd. edu/~wym/3dpose. html
no code implementations • CVPR 2014 • Xiao Tan, Changming Sun, Tuan D. Pham
By using the hybrid of the local polynomial model and color/intensity based range guidance, the proposed method not only preserves edges but also does a much better job in preserving spatial variation than existing popular filtering methods.