1 code implementation • 31 Mar 2024 • Haolin Qin, Tingfa Xu, Peifu Liu, Jingxuan Xu, Jianan Li
To address these challenges, we propose a novel approach termed the Distilled Mixed Spectral-Spatial Network (DMSSN), comprising a Distilled Spectral Encoding process and a Mixed Spectral-Spatial Transformer (MSST) feature extraction network.
no code implementations • 7 Mar 2024 • Xiaoying Yuan, Tingfa Xu, Xincong Liu, Ying Wang, Haolin Qin, Yuqiang Fang, Jianan Li
This module leverages temporal information to refresh the template feature, yielding a more precise correlation map.
1 code implementation • 22 Jan 2024 • Jianan Li, Jie Wang, Tingfa Xu
Efficient analysis of point clouds holds paramount significance in real-world 3D applications.
no code implementations • 22 Jan 2024 • Jianan Li, Shaocong Dong, Lihe Ding, Tingfa Xu
To mitigate the computational complexity associated with applying a window-based transformer in 3D voxel space, we introduce a novel Chessboard Sampling strategy and implement voxel sampling and gathering operations sparsely using a hash map.
no code implementations • 22 Jan 2024 • Shenwang Jiang, Jianan Li, Ying Wang, Wenxuan Wu, Jizhou Zhang, Bo Huang, Tingfa Xu
Noisy labels, inevitably existing in pseudo segmentation labels generated from weak object-level annotations, severely hampers model optimization for semantic segmentation.
1 code implementation • 14 Dec 2023 • Haolin Qin, Daquan Zhou, Tingfa Xu, Ziyang Bian, Jianan Li
Accordingly, we propose a novel factorization self-attention mechanism (FaSA) that enjoys both the advantages of local window cost and long-range dependency modeling capability.
no code implementations • 11 Dec 2023 • Xincong Liu, Tingfa Xu, Ying Wang, Zhinong Yu, Xiaoying Yuan, Haolin Qin, Jianan Li
At the same time, the appearance discriminator employs an online adaptive template-update strategy to ensure that the collected multiple templates remain reliable and diverse, allowing them to closely follow rapid changes in the target's appearance and suppress background interference during tracking.
no code implementations • 2 Dec 2023 • Huan Chen, Wangcai Zhao, Tingfa Xu, Shiyun Zhou, Peifu Liu, Jianan Li
The Fourier coordinate encoder enhances the SINR's ability to emphasize high-frequency components, while the spectral scale factor module guides the SINR to adapt to the variable number of spectral channels.
1 code implementation • 2 Dec 2023 • Peifu Liu, Tingfa Xu, Huan Chen, Shiyun Zhou, Haolin Qin, Jianan Li
The Spectral Saliency approximates the region of salient objects, while the Spectral Edge captures edge information of salient objects.
1 code implementation • ICCV 2023 • Jie Wang, Lihe Ding, Tingfa Xu, Shaocong Dong, Xinli Xu, Long Bai, Jianan Li
Robust 3D perception under corruption has become an essential task for the realm of 3D vision.
no code implementations • 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
no code implementations • 24 Aug 2023 • Jianan Li, Liang Li, Shiyu Zhao
The comprehension of how local interactions arise in global collective behavior is of utmost importance in both biological and physical research.
1 code implementation • 31 Jul 2023 • Tao Huang, Kai Chen, Wang Wei, Jianan Li, Yonghao Long, Qi Dou
Based on this value function, a chaining policy is learned to instruct subtask policies to terminate at the state with the highest value so that all subsequent policies are more likely to be connected for accomplishing the task.
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 • 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 • 6 Feb 2023 • Shiyun Zhou, Tingfa Xu, Shaocong Dong, Jianan Li
The regional dynamic block guides the network to adjust the transformation domain for different regions.
no code implementations • CVPR 2023 • Jianan Li, Qiulei Dong
The proposed APF consists of a feature extraction module for extracting point features, a prototypical constraint module, and a feature adversarial module.
no code implementations • CVPR 2023 • Shiqi Huang, Tingfa Xu, Ning Shen, Feng Mu, Jianan Li
The existing few-shot medical segmentation networks share the same practice that the more prototypes, the better performance.
no code implementations • 18 Dec 2022 • Jianan Li, Shenwang Jiang, Liqiang Song, Peiran Peng, Feng Mu, Hui Li, Peng Jiang, Tingfa Xu
Hence, the timely and accurate detection of surface defects is crucial for FAST's stable operation.
1 code implementation • 22 Nov 2022 • Shenwang Jiang, Jianan Li, Jizhou Zhang, Ying Wang, Tingfa Xu
Label noise and class imbalance commonly coexist in real-world data.
Ranked #6 on Learning with noisy labels on ANIMAL
1 code implementation • 9 Oct 2022 • Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, LiWei Wang
We present a novel two-stage fully sparse convolutional 3D object detection framework, named CAGroup3D.
Ranked #1 on 3D Object Detection on SUN-RGBD
no code implementations • 22 Sep 2022 • Xinli Xu, Shaocong Dong, Lihe Ding, Jie Wang, Tingfa Xu, Jianan Li
Existing 3D detectors significantly improve the accuracy by adopting a two-stage paradigm which merely relies on LiDAR point clouds for 3D proposal refinement.
no code implementations • 26 Jan 2022 • Shiqi Huang, Jianan Li, Yuze Xiao, Ning Shen, Tingfa Xu
Automatic diabetic retinopathy (DR) lesions segmentation makes great sense of assisting ophthalmologists in diagnosis.
1 code implementation • 30 Dec 2021 • Shenwang Jiang, Jianan Li, Ying Wang, Bo Huang, Zhang Zhang, Tingfa Xu
In practice, however, biased samples with corrupted labels and of tailed classes commonly co-exist in training data.
no code implementations • 28 Nov 2021 • Jie Wang, Jianan Li, Lihe Ding, Ying Wang, Tingfa Xu
Fine-grained geometry, captured by aggregation of point features in local regions, is crucial for object recognition and scene understanding in point clouds.
no code implementations • 15 Oct 2021 • Ying Wang, Tingfa Xu, Jianan Li, Shenwang Jiang, Junjie Chen
Through experiments we find that, without regression, the performance could be equally promising as long as we delicately design the network to suit the training objective.
no code implementations • 23 Aug 2021 • Jian Zhao, Gang Wang, Jianan Li, Lei Jin, Nana Fan, Min Wang, Xiaojuan Wang, Ting Yong, Yafeng Deng, Yandong Guo, Shiming Ge, Guodong Guo
The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking.
no code implementations • 30 Apr 2021 • Xinglong Sun, Guangliang Han, Lihong Guo, Tingfa Xu, Jianan Li, Peixun Liu
Offline Siamese networks have achieved very promising tracking performance, especially in accuracy and efficiency.
no code implementations • 16 Dec 2020 • Jianan Li, Xuemei Xie, Zhifu Zhao, Yuhan Cao, Qingzhe Pan, Guangming Shi
Specifically, the constructed temporal relation graph explicitly builds connections between semantically related temporal features to model temporal relations between both adjacent and non-adjacent time steps.
no code implementations • 11 Sep 2020 • Jianan Li, Jimei Yang, Jianming Zhang, Chang Liu, Christina Wang, Tingfa Xu
In this paper, we introduce Attribute-conditioned Layout GAN to incorporate the attributes of design elements for graphic layout generation by forcing both the generator and the discriminator to meet attribute conditions.
no code implementations • 4 Jul 2020 • Jianan Li, Jiashi Feng
The performance of 3D object detection models over point clouds highly depends on their capability of modeling local geometric patterns.
1 code implementation • ICLR 2019 • Jianan Li, Tingfa Xu, Jianming Zhang, Aaron Hertzmann, Jimei Yang
Layouts are important for graphic design and scene generation.
1 code implementation • 21 Jan 2019 • Jianan Li, Jimei Yang, Aaron Hertzmann, Jianming Zhang, Tingfa Xu
Layout is important for graphic design and scene generation.
no code implementations • 16 Nov 2017 • Jianshu Li, Shengtao Xiao, Fang Zhao, Jian Zhao, Jianan Li, Jiashi Feng, Shuicheng Yan, Terence Sim
Specifically, iFAN achieves an overall F-score of 91. 15% on the Helen dataset for face parsing, a normalized mean error of 5. 81% on the MTFL dataset for facial landmark localization and an accuracy of 45. 73% on the BNU dataset for emotion recognition with a single model.
19 code implementations • NeurIPS 2017 • Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng
In this work, we present a simple, highly efficient and modularized Dual Path Network (DPN) for image classification which presents a new topology of connection paths internally.
no code implementations • CVPR 2017 • Jianan Li, Xiaodan Liang, Yunchao Wei, Tingfa Xu, Jiashi Feng, Shuicheng Yan
In this work, we address the small object detection problem by developing a single architecture that internally lifts representations of small objects to "super-resolved" ones, achieving similar characteristics as large objects and thus more discriminative for detection.
no code implementations • 18 Aug 2016 • Jianan Li, Xiaodan Liang, Jianshu Li, Tingfa Xu, Jiashi Feng, Shuicheng Yan
Most of existing detection pipelines treat object proposals independently and predict bounding box locations and classification scores over them separately.
no code implementations • 24 Mar 2016 • Jianan Li, Yunchao Wei, Xiaodan Liang, Jian Dong, Tingfa Xu, Jiashi Feng, Shuicheng Yan
We provide preliminary answers to these questions through developing a novel Attention to Context Convolution Neural Network (AC-CNN) based object detection model.
1 code implementation • 26 Feb 2016 • Wei Han, Pooya Khorrami, Tom Le Paine, Prajit Ramachandran, Mohammad Babaeizadeh, Honghui Shi, Jianan Li, Shuicheng Yan, Thomas S. Huang
Video object detection is challenging because objects that are easily detected in one frame may be difficult to detect in another frame within the same clip.
no code implementations • 28 Oct 2015 • Jianan Li, Xiaodan Liang, ShengMei Shen, Tingfa Xu, Jiashi Feng, Shuicheng Yan
Taking pedestrian detection as an example, we illustrate how we can leverage this philosophy to develop a Scale-Aware Fast R-CNN (SAF R-CNN) framework.
Ranked #23 on Pedestrian Detection on Caltech