no code implementations • ECCV 2020 • Yunhang Shen, Rongrong Ji, Yan Wang, Zhiwei Chen, Feng Zheng, Feiyue Huang, Yunsheng Wu
Weakly supervised object detection (WSOD) has attracted extensive research attention due to its great flexibility of exploiting large-scale image-level annotation for detector training.
no code implementations • 6 Jun 2024 • Yixuan Yang, Junru Lu, Zixiang Zhao, Zhen Luo, James J. Q. Yu, Victor Sanchez, Feng Zheng
In this paper, we introduce LLplace, a novel 3D indoor scene layout designer based on lightweight fine-tuned open-source LLM Llama3.
no code implementations • 27 May 2024 • Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei
In this work, we show that, on text generation tasks, noisy annotations significantly hurt the performance of in-context learning.
no code implementations • 26 Apr 2024 • Xinpeng Li, Teng Wang, Jian Zhao, Shuyi Mao, Jinbao Wang, Feng Zheng, Xiaojiang Peng, Xuelong Li
Emotion recognition aims to discern the emotional state of subjects within an image, relying on subject-centric and contextual visual cues.
1 code implementation • 4 Apr 2024 • Tiantian Geng, Teng Wang, yanfu Zhang, Jinming Duan, Weili Guan, Feng Zheng
Video localization tasks aim to temporally locate specific instances in videos, including temporal action localization (TAL), sound event detection (SED) and audio-visual event localization (AVEL).
1 code implementation • 29 Mar 2024 • Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
In this paper, we propose a novel post hoc OOD detection method, called NegLabel, which takes a vast number of negative labels from extensive corpus databases.
no code implementations • 21 Mar 2024 • Xi Jiang, Ying Chen, Qiang Nie, Jianlin Liu, Yong liu, Chengjie Wang, Feng Zheng
To address this issue, we introduce a Multi-class Implicit Neural representation Transformer for unified Anomaly Detection (MINT-AD), which leverages the fine-grained category information in the training stage.
1 code implementation • NeurIPS 2022 • Xi Jiang, Ying Chen, Qiang Nie, Yong liu, Jianlin Liu, Bin-Bin Gao, Jun Liu, Chengjie Wang, Feng Zheng
Noise discriminators are utilized to generate outlier scores for patch-level noise elimination before coreset construction.
no code implementations • 19 Mar 2024 • Pengzhi Li, Qiang Nie, Ying Chen, Xi Jiang, Kai Wu, Yuhuan Lin, Yong liu, Jinlong Peng, Chengjie Wang, Feng Zheng
To our knowledge, this is the first tuning-free method that concurrently utilizes text and image guidance for image customization in specific regions.
no code implementations • 22 Feb 2024 • Ziling Liu, Jinyu Yang, Mingqi Gao, Feng Zheng
This paper introduces a novel and efficient system named Place-Anything, which facilitates the insertion of any object into any video solely based on a picture or text description of the target object or element.
1 code implementation • 2 Jan 2024 • Jiaqi Liu, Kai Wu, Qiang Nie, Ying Chen, Bin-Bin Gao, Yong liu, Jinbao Wang, Chengjie Wang, Feng Zheng
Unsupervised Anomaly Detection (UAD) with incremental training is crucial in industrial manufacturing, as unpredictable defects make obtaining sufficient labeled data infeasible.
1 code implementation • 29 Dec 2023 • Yunlong Tang, Jing Bi, Siting Xu, Luchuan Song, Susan Liang, Teng Wang, Daoan Zhang, Jie An, Jingyang Lin, Rongyi Zhu, Ali Vosoughi, Chao Huang, Zeliang Zhang, Feng Zheng, JianGuo Zhang, Ping Luo, Jiebo Luo, Chenliang Xu
With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly.
1 code implementation • 19 Dec 2023 • Yanqi Ge, Qiang Nie, Ye Huang, Yong liu, Chengjie Wang, Feng Zheng, Wen Li, Lixin Duan
By pulling the learned features to these semantic anchors, several advantages can be attained: 1) the intra-class compactness and naturally inter-class separability, 2) induced bias or errors from feature learning can be avoided, and 3) robustness to the long-tailed problem.
1 code implementation • NeurIPS 2023 • Jiaqi Liu, Guoyang Xie, Ruitao Chen, Xinpeng Li, Jinbao Wang, Yong liu, Chengjie Wang, Feng Zheng
High-precision point cloud anomaly detection is the gold standard for identifying the defects of advancing machining and precision manufacturing.
1 code implementation • ICCV 2023 • Guanghui Li, Mingqi Gao, Heng Liu, XianTong Zhen, Feng Zheng
Referring video object segmentation (RVOS), as a supervised learning task, relies on sufficient annotated data for a given scene.
Referring Video Object Segmentation Semantic Segmentation +1
no code implementations • ICCV 2023 • Baoshuo Kan, Teng Wang, Wenpeng Lu, XianTong Zhen, Weili Guan, Feng Zheng
Pre-trained vision-language models, e. g., CLIP, working with manually designed prompts have demonstrated great capacity of transfer learning.
2 code implementations • 17 Aug 2023 • Runmin Cong, Hongyu Liu, Chen Zhang, Wei zhang, Feng Zheng, Ran Song, Sam Kwong
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved.
1 code implementation • ICCV 2023 • Junjie Fei, Teng Wang, Jinrui Zhang, Zhenyu He, Chengjie Wang, Feng Zheng
In this paper, we propose ViECap, a transferable decoding model that leverages entity-aware decoding to generate descriptions in both seen and unseen scenarios.
1 code implementation • ICCV 2023 • Dong Lu, Zhiqiang Wang, Teng Wang, Weili Guan, Hongchang Gao, Feng Zheng
Vision-language pre-training (VLP) models have shown vulnerability to adversarial examples in multimodal tasks.
no code implementations • 26 Jul 2023 • Ruitao Chen, Guoyang Xie, Jiaqi Liu, Jinbao Wang, Ziqi Luo, Jinfan Wang, Feng Zheng
3D anomaly detection is an emerging and vital computer vision task in industrial manufacturing (IM).
no code implementations • 10 Jul 2023 • Guoyang Xie, Jinbao Wang, Yawen Huang, Jiayi Lyu, Feng Zheng, Yefeng Zheng, Yaochu Jin
To further reflect the frequency-specific information from the magnetic resonance imaging principles, both k-space features and vision features are obtained and employed in our comprehensive encoders with a frequency reconstruction penalty.
1 code implementation • 7 Jul 2023 • Siting Xu, Yunlong Tang, Feng Zheng
To assist and inspire the design of the Launchpad light effect, and provide a more accessible approach for beginners to create music visualization with this instrument, we proposed the LaunchpadGPT model to generate music visualization designs on Launchpad automatically.
1 code implementation • 17 Jun 2023 • Yunlong Tang, Jinrui Zhang, Xiangchen Wang, Teng Wang, Feng Zheng
This paper proposes an effective model LLMVA-GEBC (Large Language Model with Video Adapter for Generic Event Boundary Captioning): (1) We utilize a pretrained LLM for generating human-like captions with high quality.
no code implementations • 17 May 2023 • Hao Zheng, Jinbao Wang, XianTong Zhen, Hong Chen, Jingkuan Song, Feng Zheng
Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input sequence.
1 code implementation • ICML 2023 • Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
In this paper, we show that this assumption makes the above methods incapable when the ID model is trained with class-imbalanced data. Fortunately, by analyzing the causal relations between ID/OOD classes and features, we identify several common scenarios where the OOD-to-ID probabilities should be the ID-class-prior distribution and propose two strategies to modify existing inference-time detection methods: 1) replace the uniform distribution with the ID-class-prior distribution if they explicitly use the uniform distribution; 2) otherwise, reweight their scores according to the similarity between the ID-class-prior distribution and the softmax outputs of the pre-trained model.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • 24 Apr 2023 • Jinyu Yang, Mingqi Gao, Zhe Li, Shang Gao, Fangjing Wang, Feng Zheng
Therefore, in this report, we propose Track Anything Model (TAM), which achieves high-performance interactive tracking and segmentation in videos.
no code implementations • 24 Apr 2023 • Yihan Zhang, Wenhao Jiang, Feng Zheng, Chiu C. Tan, Xinghua Shi, Hongchang Gao
This motivates us to study decentralized minimax optimization algorithms for the nonconvex-nonconcave problem.
no code implementations • 6 Apr 2023 • Lingrui Zhang, Shuheng Zhang, Guoyang Xie, Jiaqi Liu, Hua Yan, Jinbao Wang, Feng Zheng, Yaochu Jin
Data augmentation is a promising technique for unsupervised anomaly detection in industrial applications, where the availability of positive samples is often limited due to factors such as commercial competition and sample collection difficulties.
1 code implementation • CVPR 2023 • Teng Wang, Yixiao Ge, Feng Zheng, Ran Cheng, Ying Shan, XiaoHu Qie, Ping Luo
FLM successfully frees the prediction rate from the tie-up with the corruption rate while allowing the corruption spans to be customized for each token to be predicted.
1 code implementation • CVPR 2023 • Tiantian Geng, Teng Wang, Jinming Duan, Runmin Cong, Feng Zheng
To better adapt to real-life applications, in this paper we focus on the task of dense-localizing audio-visual events, which aims to jointly localize and recognize all audio-visual events occurring in an untrimmed video.
Ranked #1 on audio-visual event localization on UnAV-100
1 code implementation • 11 Mar 2023 • Teng Wang, Jinrui Zhang, Feng Zheng, Wenhao Jiang, Ran Cheng, Ping Luo
Our framework is easily extensible to tasks covering visually-grounded language understanding and generation.
no code implementations • 20 Feb 2023 • Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng
Triplet learning, i. e. learning from triplet data, has attracted much attention in computer vision tasks with an extremely large number of categories, e. g., face recognition and person re-identification.
2 code implementations • 31 Jan 2023 • Guoyang Xie, Jinbao Wang, Jiaqi Liu, Jiayi Lyu, Yong liu, Chengjie Wang, Feng Zheng, Yaochu Jin
We realize that the lack of a uniform IM benchmark is hindering the development and usage of IAD methods in real-world applications.
no code implementations • 28 Jan 2023 • Guoyang Xie, Jinbao Wang, Jiaqi Liu, Feng Zheng, Yaochu Jin
Besides, we provide a novel model GraphCore via VIIFs that can fast implement unsupervised FSAD training and can improve the performance of anomaly detection.
1 code implementation • 27 Jan 2023 • Jiaqi Liu, Guoyang Xie, Jinbao Wang, Shangnian Li, Chengjie Wang, Feng Zheng, Yaochu Jin
In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural network architectures, levels of supervision, loss functions, metrics and datasets.
1 code implementation • CVPR 2023 • Jinyu Yang, Shang Gao, Zhe Li, Feng Zheng, Aleš Leonardis
However, current research on aerial perception has mainly focused on limited categories, such as pedestrian or vehicle, and most scenes are captured in urban environments from a birds-eye view.
no code implementations • 6 Nov 2022 • Shang Gao, Jinyu Yang, Zhe Li, Feng Zheng, Aleš Leonardis, Jingkuan Song
However, some existing RGBD trackers use the two modalities separately and thus some particularly useful shared information between them is ignored.
1 code implementation • ACMMM 2022 • Wujin Li, Jiawei Zhan, Jinbao Wang, Bizhong Xia, Bin-Bin Gao, Jun Liu, Chengjie Wang, Feng Zheng
We believe that the proposed task and benchmark will be beneficial to the field of AD.
2 code implementations • 9 Oct 2022 • Runmin Cong, Kepu Zhang, Chen Zhang, Feng Zheng, Yao Zhao, Qingming Huang, Sam Kwong
In addition, considering the role of thermal modality, we set up different cross-modality interaction mechanisms in the encoding phase and the decoding phase.
no code implementations • 26 Sep 2022 • Yufeng Shi, Xinge You, Jiamiao Xu, Feng Zheng, Qinmu Peng, Weihua Ou
Hashing that projects data into binary codes has shown extraordinary talents in cross-modal retrieval due to its low storage usage and high query speed.
1 code implementation • 25 Sep 2022 • Yunlong Tang, Siting Xu, Teng Wang, Qin Lin, Qinglin Lu, Feng Zheng
The existing method performs well at video segmentation stages but suffers from the problems of dependencies on extra cumbersome models and poor performance at the segment assemblage stage.
no code implementations • 23 Sep 2022 • Honghu Pan, Qiao Liu, Yongyong Chen, Yunqi He, Yuan Zheng, Feng Zheng, Zhenyu He
Finally, we propose a dual-attention method consisting of node-attention and time-attention to obtain the temporal graph representation from the node embeddings, where the self-attention mechanism is employed to learn the importance of each node and each frame.
no code implementations • TIP 2022 • Tiantian Geng, Feng Zheng, Xiaorong Hou, Ke Lu, Guo-Jun Qi, Ling Shao
Spatial-temporal relation reasoning is a significant yet challenging problem for video action recognition.
Ranked #35 on Action Recognition on Something-Something V1
no code implementations • 1 Aug 2022 • Tze Ho Elden Tse, Zhongqun Zhang, Kwang In Kim, Ales Leonardis, Feng Zheng, Hyung Jin Chang
In this paper, we propose a novel semi-supervised framework that allows us to learn contact from monocular images.
no code implementations • 29 Jul 2022 • Jinyu Yang, Zhe Li, Feng Zheng, Aleš Leonardis, Jingkuan Song
Multi-modal tracking gains attention due to its ability to be more accurate and robust in complex scenarios compared to traditional RGB-based tracking.
Ranked #21 on Rgb-T Tracking on LasHeR
1 code implementation • 3 Jul 2022 • Jinrui Zhang, Teng Wang, Feng Zheng, Ran Cheng, Ping Luo
Previous methods only process the information of a single boundary at a time, which lacks utilization of video context information.
1 code implementation • 17 Jun 2022 • Teng Wang, Wenhao Jiang, Zhichao Lu, Feng Zheng, Ran Cheng, Chengguo Yin, Ping Luo
Existing vision-language pre-training (VLP) methods primarily rely on paired image-text datasets, which are either annotated by enormous human labors, or crawled from the internet followed by elaborate data cleaning techniques.
no code implementations • 25 Apr 2022 • Minghui Chen, Cheng Wen, Feng Zheng, Fengxiang He, Ling Shao
The tangent transfer creates initial augmented samples for improving corruption robustness.
no code implementations • 13 Apr 2022 • Teng Wang, Zhu Liu, Feng Zheng, Zhichao Lu, Ran Cheng, Ping Luo
This report describes the details of our approach for the event dense-captioning task in ActivityNet Challenge 2021.
1 code implementation • 26 Mar 2022 • Jinyu Yang, Zhe Li, Song Yan, Feng Zheng, Aleš Leonardis, Joni-Kristian Kämäräinen, Ling Shao
Particularly, we are the first to provide depth quality evaluation and analysis of tracking results in depth-friendly scenarios in RGBD tracking.
1 code implementation • CVPR 2022 • Xiaosu Zhu, Jingkuan Song, Lianli Gao, Feng Zheng, Heng Tao Shen
Modeling latent variables with priors and hyperpriors is an essential problem in variational image compression.
no code implementations • 9 Mar 2022 • Xuebin Zhao, Hong Chen, Yingjie Wang, Weifu Li, Tieliang Gong, Yulong Wang, Feng Zheng
Recently, the scheme of model-X knockoffs was proposed as a promising solution to address controlled feature selection under high-dimensional finite-sample settings.
1 code implementation • 8 Mar 2022 • Jingfei Xia, Mingchen Zhuge, Tiantian Geng, Shun Fan, Yuantai Wei, Zhenyu He, Feng Zheng
Figure skating scoring is challenging because it requires judging the technical moves of the players as well as their coordination with the background music.
1 code implementation • CVPR 2022 • Fan Yang, Kai Wu, Shuyi Zhang, Guannan Jiang, Yong liu, Feng Zheng, Wei zhang, Chengjie Wang, Long Zeng
Pseudo-label-based semi-supervised learning (SSL) has achieved great success on raw data utilization.
1 code implementation • 14 Feb 2022 • Xi Jiang, Guoyang Xie, Jinbao Wang, Yong liu, Chengjie Wang, Feng Zheng, Yaochu Jin
In this survey, we are the first one to provide a comprehensive review of visual sensory AD and category into three levels according to the form of anomalies.
no code implementations • 14 Feb 2022 • Guoyang Xie, Yawen Huang, Jinbao Wang, Jiayi Lyu, Feng Zheng, Yefeng Zheng, Yaochu Jin
This is followed by a stepwise in-depth analysis to evaluate how cross-modality neuroimage synthesis improves the performance of its downstream tasks.
1 code implementation • 29 Jan 2022 • Jinbao Wang, Guoyang Xie, Yawen Huang, Yefeng Zheng, Yaochu Jin, Feng Zheng
The proposed method demonstrates the advanced performance in both the quality of our synthesized results under a severely misaligned and unpaired data setting, and better stability than other GAN-based algorithms.
1 code implementation • 22 Jan 2022 • Jinbao Wang, Guoyang Xie, Yawen Huang, Jiayi Lyu, Yefeng Zheng, Feng Zheng, Yaochu Jin
There is a clear need to launch a federated learning and facilitate the integration of the dispersed data from different institutions.
1 code implementation • CVPR 2022 • Hao Ni, Jingkuan Song, Xiaopeng Luo, Feng Zheng, Wen Li, Heng Tao Shen
Domain Generalizable (DG) person ReID is a challenging task which trains a model on source domains yet generalizes well on target domains.
no code implementations • 28 Dec 2021 • Peng Tu, Yawen Huang, Feng Zheng, Zhenyu He, Liujun Cao, Ling Shao
In this paper, we propose a novel method for semi-supervised semantic segmentation named GuidedMix-Net, by leveraging labeled information to guide the learning of unlabeled instances.
1 code implementation • 1 Nov 2021 • Minghui Chen, Zhiqiang Wang, Feng Zheng
When deploying person re-identification (ReID) model in safety-critical applications, it is pivotal to understanding the robustness of the model against a diverse array of image corruptions.
Ranked #1 on Cross-Modal Person Re-Identification on RegDB-C (mINP (Visible to Thermal) metric)
Cross-Modal Person Re-Identification Generalizable Person Re-identification
1 code implementation • 31 Aug 2021 • Song Yan, Jinyu Yang, Jani Käpylä, Feng Zheng, Aleš Leonardis, Joni-Kristian Kämäräinen
RGBD (RGB plus depth) object tracking is gaining momentum as RGBD sensors have become popular in many application fields such as robotics. However, the best RGBD trackers are extensions of the state-of-the-art deep RGB trackers.
no code implementations • ICCV 2021 • Hongjun Chen, Jinbao Wang, Hong Cai Chen, XianTong Zhen, Feng Zheng, Rongrong Ji, Ling Shao
Annotation burden has become one of the biggest barriers to semantic segmentation.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
2 code implementations • ICCV 2021 • Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, Ping Luo
Dense video captioning aims to generate multiple associated captions with their temporal locations from the video.
Ranked #5 on Dense Video Captioning on YouCook2
no code implementations • 13 Aug 2021 • YiCheng Pan, Feng Zheng, Bingchen Fan
In this paper, we investigate hierarchical clustering from the \emph{information-theoretic} perspective and formulate a new objective function.
1 code implementation • ICCV 2021 • Zikun Zhou, Wenjie Pei, Xin Li, Hongpeng Wang, Feng Zheng, Zhenyu He
A potential limitation of such trackers is that not all patches are equally informative for tracking.
1 code implementation • ICCV 2021 • Shiming Chen, Wenjie Wang, Beihao Xia, Qinmu Peng, Xinge You, Feng Zheng, Ling Shao
FREE employs a feature refinement (FR) module that incorporates \textit{semantic$\rightarrow$visual} mapping into a unified generative model to refine the visual features of seen and unseen class samples.
no code implementations • 7 Jul 2021 • Peidong Liu, Zibin He, Xiyu Yan, Yong Jiang, Shutao Xia, Feng Zheng, Maowei Hu
In this work, we propose an effective weakly-supervised video semantic segmentation pipeline with click annotations, called WeClick, for saving laborious annotating effort by segmenting an instance of the semantic class with only a single click.
1 code implementation • 29 Jun 2021 • Peng Tu, Yawen Huang, Rongrong Ji, Feng Zheng, Ling Shao
To take advantage of the labeled examples and guide unlabeled data learning, we further propose a mask generation module to generate high-quality pseudo masks for the unlabeled data.
1 code implementation • CVPR 2021 • Jiaxing Chen, Xinyang Jiang, Fudong Wang, Jun Zhang, Feng Zheng, Xing Sun, Wei-Shi Zheng
In this paper, rather than relying on texture based information, we propose to improve the robustness of person ReID against clothing texture by exploiting the information of a person's 3D shape.
Ranked #4 on Person Re-Identification on PRCC
no code implementations • CVPR 2021 • Yawen Huang, Feng Zheng, Danyang Wang, Weilin Huang, Matthew R. Scott, Ling Shao
Recent advances in neuroscience have highlighted the effectiveness of multi-modal medical data for investigating certain pathologies and understanding human cognition.
no code implementations • 22 Mar 2021 • Yawen Huang, Feng Zheng, Danyang Wang, Weilin Huang, Matthew R. Scott, Ling Shao
Recent advances in neuroscience have highlighted the effectiveness of multi-modal medical data for investigating certain pathologies and understanding human cognition.
no code implementations • 28 Feb 2021 • Guoyang Xie, Jinbao Wang, Guo Yu, Feng Zheng, Yaochu Jin
Our work focuses on how to improve the robustness of tiny neural networks without seriously deteriorating of clean accuracy under mobile-level resources.
no code implementations • 3 Feb 2021 • Liangxi Liu, Xi Jiang, Feng Zheng, Hong Chen, Guo-Jun Qi, Heng Huang, Ling Shao
On the client side, a prior loss that uses the global posterior probabilistic parameters delivered from the server is designed to guide the local training.
2 code implementations • 8 Jan 2021 • Chenyang Gao, Guanyu Cai, Xinyang Jiang, Feng Zheng, Jun Zhang, Yifei Gong, Pai Peng, Xiaowei Guo, Xing Sun
Secondly, a BERT with locality-constrained attention is proposed to obtain representations of descriptions at different scales.
Ranked #15 on Text based Person Retrieval on CUHK-PEDES
1 code implementation • ICCV 2021 • Song Yan, Jinyu Yang, Jani Kapyla, Feng Zheng, Ales Leonardis, Joni-Kristian Kamarainen
This can be explained by the fact that there are no sufficiently large RGBD datasets to 1) train "deep depth trackers" and to 2) challenge RGB trackers with sequences for which the depth cue is essential.
1 code implementation • 10 Dec 2020 • Enwei Zhang, Xinyang Jiang, Hao Cheng, AnCong Wu, Fufu Yu, Ke Li, Xiaowei Guo, Feng Zheng, Wei-Shi Zheng, Xing Sun
Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the performance on samples outside the batch.
no code implementations • NeurIPS 2020 • Yingjie Wang, Hong Chen, Feng Zheng, Chen Xu, Tieliang Gong, Yanhong Chen
For high-dimensional observations in real environment, e. g., Coronal Mass Ejections (CMEs) data, the learning performance of previous methods may be degraded seriously due to the complex non-Gaussian noise and the insufficiency of prior knowledge on variable structure.
no code implementations • 2 Oct 2020 • Chongyi Li, Runmin Cong, Chunle Guo, Hua Li, Chunjie Zhang, Feng Zheng, Yao Zhao
In this paper, we propose a novel Parallel Down-up Fusion network (PDF-Net) for SOD in optical RSIs, which takes full advantage of the in-path low- and high-level features and cross-path multi-resolution features to distinguish diversely scaled salient objects and suppress the cluttered backgrounds.
1 code implementation • 11 Sep 2020 • Fufu Yu, Xinyang Jiang, Yifei Gong, Shizhen Zhao, Xiaowei Guo, Wei-Shi Zheng, Feng Zheng, Xing Sun
Secondly, the Conditional Feature Embedding requires the overall feature of a query image to be dynamically adjusted based on the gallery image it matches, while most of the existing methods ignore the reference images.
Ranked #1 on Person Re-Identification on CUHK03-C
1 code implementation • 3 Aug 2020 • Qiao Liu, Xin Li, Zhenyu He, Chenglong Li, Jun Li, Zikun Zhou, Di Yuan, Jing Li, Kai Yang, Nana Fan, Feng Zheng
We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance.
Thermal Infrared Object Tracking Vocal Bursts Intensity Prediction
1 code implementation • 27 Jul 2020 • Peixian Chen, Pingyang Dai, Jianzhuang Liu, Feng Zheng, Qi Tian, Rongrong Ji
Domain generalization (DG) serves as a promising solution to handle person Re-Identification (Re-ID), which trains the model using labels from the source domain alone, and then directly adopts the trained model to the target domain without model updating.
Domain Generalization Generalizable Person Re-identification
no code implementations • 20 Mar 2020 • Rui Xiang, Feng Zheng, Huapeng Su, Zhe Zhang
In this paper, we propose an end-to-end deep learning network named 3dDepthNet, which produces an accurate dense depth image from a single pair of sparse LiDAR depth and color image for robotics and autonomous driving tasks.
1 code implementation • 3 Dec 2019 • Zhihui Zhu, Xinyang Jiang, Feng Zheng, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng, Xing Sun
Instead of one subspace for each viewpoint, our method projects the feature from different viewpoints into a unified hypersphere and effectively models the feature distribution on both the identity-level and the viewpoint-level.
Ranked #5 on Person Re-Identification on Market-1501 (using extra training data)
2 code implementations • 28 Nov 2019 • Xinyang Jiang, Yifei Gong, Xiaowei Guo, Qize Yang, Feiyue Huang, Wei-Shi Zheng, Feng Zheng, Xing Sun
Recently, the research interest of person re-identification (ReID) has gradually turned to video-based methods, which acquire a person representation by aggregating frame features of an entire video.
no code implementations • 31 May 2019 • Mingbao Lin, Rongrong Ji, Shen Chen, Feng Zheng, Xiaoshuai Sun, Baochang Zhang, Liujuan Cao, Guodong Guo, Feiyue Huang
In this paper, we propose to model the similarity distributions between the input data and the hashing codes, upon which a novel supervised online hashing method, dubbed as Similarity Distribution based Online Hashing (SDOH), is proposed, to keep the intrinsic semantic relationship in the produced Hamming space.
no code implementations • CVPR 2019 • Xu Yang, Cheng Deng, Feng Zheng, Junchi Yan, Wei Liu
In this paper, we propose a joint learning framework for discriminative embedding and spectral clustering.
1 code implementation • CVPR 2019 • Feng Zheng, Cheng Deng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang, Rongrong Ji
Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other.
Ranked #2 on Person Re-Identification on CUHK03-C
no code implementations • CVPR 2018 • Kamran Ghasedi Dizaji, Feng Zheng, Najmeh Sadoughi, Yanhua Yang, Cheng Deng, Heng Huang
HashGAN consists of three networks, a generator, a discriminator and an encoder.
no code implementations • 6 Mar 2018 • Feng Zheng, Grace Tsai, Zhe Zhang, Shaoshan Liu, Chen-Chi Chu, Hongbing Hu
In this paper, we present the Trifo Visual Inertial Odometry (Trifo-VIO), a tightly-coupled filtering-based stereo VIO system using both points and lines.
no code implementations • 2 Oct 2017 • Zhe Zhang, Shaoshan Liu, Grace Tsai, Hongbing Hu, Chen-Chi Chu, Feng Zheng
In this paper, we present the PerceptIn Robotics Vision System (PIRVS) system, a visual-inertial computing hardware with embedded simultaneous localization and mapping (SLAM) algorithm.
no code implementations • 2 Jun 2017 • BingZhang Hu, Feng Zheng, Ling Shao
Face retrieval has received much attention over the past few decades, and many efforts have been made in retrieving face images against pose, illumination, and expression variations.