2 code implementations • ECCV 2020 • Xiaotong Luo, Yuan Xie, Yulun Zhang, Yanyun Qu, Cuihua Li, Yun Fu
Drawing lessons from lattice filter bank, we design the lattice block (LB) in which two butterfly structures are applied to combine two RBs.
1 code implementation • 27 Feb 2025 • Xiaofan Li, Xin Tan, Zhuo Chen, Zhizhong Zhang, Ruixin Zhang, rizen guo, Guanna Jiang, Yulong Chen, Yanyun Qu, Lizhuang Ma, Yuan Xie
Finally, considering the risk of ``over-fitting'' to normal images of the diffusion model, we propose an anomaly-masked network to enhance the condition mechanism of the diffusion model.
no code implementations • 5 Dec 2024 • Zuo Zuo, Jiahao Dong, Yao Wu, Yanyun Qu, Zongze Wu
Then these modality-specific embeddings are used to enhance original representations of CLIP for better matching ability.
1 code implementation • 25 Oct 2024 • Yao Wu, Mingwei Xing, Yachao Zhang, Yuan Xie, Yanyun Qu
In cross-modal unsupervised domain adaptation, a model trained on source-domain data (e. g., synthetic) is adapted to target-domain data (e. g., real-world) without access to target annotation.
no code implementations • 8 Oct 2024 • Jingyang Qiao, Zhizhong Zhang, Xin Tan, Yanyun Qu, Shouhong Ding, Yuan Xie
We observe existing gradient update would heavily destroy the tuning performance on previous datasets and the zero-shot ability during continual instruction tuning.
no code implementations • 5 Sep 2024 • Pei Wang, Xiaotong Luo, Yuan Xie, Yanyun Qu
Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devices.
no code implementations • 17 Jul 2024 • Zhizhong Zhang, Jiangming Wang, Xin Tan, Yanyun Qu, JunPing Wang, Yong Xie, Yuan Xie
In the training stage, we utilize this matching information to introduce prototype-based contrastive learning for minimizing the intra- and cross-modality entropy ("Sharpness").
no code implementations • 10 Jul 2024 • Tianfang Sun, Zhizhong Zhang, Xin Tan, Yanyun Qu, Yuan Xie
We utilized timestamps and the semantic priors from VFMs to identify well-synchronized training pairs and to discover samples with diverse content.
no code implementations • 27 Jun 2024 • Zuo Zuo, Jiahao Dong, Yao Wu, Yanyun Qu, Zongze Wu
Specifically, we synthesize anomalous images on given normal images as sample pairs to adapt CLIP for 3D anomaly classification and segmentation.
no code implementations • 22 May 2024 • Jingyang Qiao, Zhizhong Zhang, Xin Tan, Yanyun Qu, Wensheng Zhang, Zhi Han, Yuan Xie
Parameter-efficient tunings (PETs) have demonstrated impressive performance and promising perspectives in training large models, while they are still confronted with a common problem: the trade-off between learning new content and protecting old knowledge, leading to zero-shot generalization collapse, and cross-modal hallucination.
1 code implementation • CVPR 2024 • Haoming Chen, Zhizhong Zhang, Yanyun Qu, Ruixin Zhang, Xin Tan, Yuan Xie
Such inconsiderate consistency greatly hampers the promising path of reaching an universal pre-training framework: (1) The cross-scene semantic self-conflict, i. e., the intense collision between primitive segments of the same semantics from different scenes; (2) Lacking a globally unified bond that pushes the cross-scene semantic consistency into 3D representation learning.
no code implementations • 9 May 2024 • Xiangbo Yin, Jiangming Shi, Yachao Zhang, Yang Lu, Zhizhong Zhang, Yuan Xie, Yanyun Qu
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable challenge, which aims to match pedestrian images across visible and infrared modalities without any annotations.
1 code implementation • CVPR 2024 • Xiaofan Li, Zhizhong Zhang, Xin Tan, Chengwei Chen, Yanyun Qu, Yuan Xie, Lizhuang Ma
The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering.
1 code implementation • 29 Feb 2024 • Jiangming Shi, Xiangbo Yin, Yachao Zhang, Zhizhong Zhang, Yuan Xie, Yanyun Qu
To address the problem, we propose a Progressive Contrastive Learning with Hard and Dynamic Prototypes method for USVI-ReID.
1 code implementation • 12 Jan 2024 • Jiangming Shi, Xiangbo Yin, Yeyun Chen, Yachao Zhang, Zhizhong Zhang, Yuan Xie, Yanyun Qu
To associate cross-modality clustered pseudo-labels, we design a Multi-Memory Learning and Matching (MMLM) module, ensuring that optimization explicitly focuses on the nuances of individual perspectives and establishes reliable cross-modality correspondences.
1 code implementation • 14 Dec 2023 • Jiangming Shi, Shanshan Zheng, Xiangbo Yin, Yang Lu, Yuan Xie, Yanyun Qu
For server-side learning, in order to mitigate the heterogeneity and class-distribution imbalance, we generate federated features to retrain the server model.
no code implementations • 13 Dec 2023 • Yujun Chen, Xin Tan, Zhizhong Zhang, Yanyun Qu, Yuan Xie
Second, in the Image Branch, we propose the Instance Position-scale Learning (IPSL) Module to learn and fuse the information of instance position and scale, which is from a 2D pre-trained detector and a type of latent label obtained from 3D to 2D projection.
1 code implementation • CVPR 2024 • Qihang Ma, Xin Tan, Yanyun Qu, Lizhuang Ma, Zhizhong Zhang, Yuan Xie
The autonomous driving community has shown significant interest in 3D occupancy prediction, driven by its exceptional geometric perception and general object recognition capabilities.
1 code implementation • journal 2023 • Zhong Chen, Zhizhong Zhang, Xin Tan, Yanyun Qu, and Yuan XieAuthors Info & Claims
In this paper, we propose a new prompt learning paradigm for unsupervised visible-infrared person re-identification (USL-VI-ReID) by taking full advantage of the visual-text representation ability from CLIP.
no code implementations • ICCV 2023 • Miaoyu Li, Yachao Zhang, Xu Ma, Yanyun Qu, Yun Fu
In light of this, we propose cross-modal learning under bird's-eye view for Domain Generalization (DG) of 3D semantic segmentation, called BEV-DG.
1 code implementation • ICCV 2023 • Jiangming Shi, Yachao Zhang, Xiangbo Yin, Yuan Xie, Zhizhong Zhang, Jianping Fan, Zhongchao shi, Yanyun Qu
Visible-infrared person re-identification (VI-ReID) aims to match a specific person from a gallery of images captured from non-overlapping visible and infrared cameras.
no code implementations • CVPR 2023 • Tenghao Cai, Zhizhong Zhang, Xin Tan, Yanyun Qu, Guannan Jiang, Chengjie Wang, Yuan Xie
As a result, our dynamic inference network is trained independently of baseline and provides a flexible, efficient solution to distinguish between tasks.
no code implementations • ICCV 2023 • Yuxiang Lan, Yachao Zhang, Xu Ma, Yanyun Qu, Yun Fu
Spiking Neural Networks (SNNs) have attracted enormous research interest due to their low-power and biologically plausible nature.
no code implementations • ICCV 2023 • Xudong Tian, Zhizhong Zhang, Xin Tan, Jun Liu, Chengjie Wang, Yanyun Qu, Guannan Jiang, Yuan Xie
Continual Learning (CL) is the constant development of complex behaviors by building upon previously acquired skills.
no code implementations • CVPR 2023 • Zhen Zhao, Zhizhong Zhang, Xin Tan, Jun Liu, Yanyun Qu, Yuan Xie, Lizhuang Ma
In this paper, we propose a space decoupling (SD) algorithm to decouple the feature space into a pair of complementary subspaces, i. e., the stability space I, and the plasticity space R. I is established by conducting space intersection between the historic and current feature space, and thus I contains more task-shared bases.
no code implementations • CVPR 2023 • Jin Lin, Xiaotong Luo, Ming Hong, Yanyun Qu, Yuan Xie, Zongze Wu
In the forward stage, we take advantage of LTH with rewinding weights to progressively shrink the SR model and the pruning-out masks that form nested sets.
4 code implementations • AAAI 2021 • Yachao Zhang, Zonghao Li, Yuan Xie, Yanyun Qu, Cuihua Li, Tao Mei
Firstly, we construct a pretext task, \textit{i. e.,} point cloud colorization, with a self-supervised learning to transfer the learned prior knowledge from a large amount of unlabeled point cloud to a weakly supervised network.
1 code implementation • 16 Sep 2022 • Tianfang Sun, Zhizhong Zhang, Xin Tan, Yanyun Qu, Yuan Xie, Lizhuang Ma
In this paper, we propose a novel cross-modality weakly supervised method for 3D segmentation, incorporating complementary information from unlabeled images.
3 code implementations • 20 Jun 2022 • Xudong Tian, Zhizhong Zhang, Cong Wang, Wensheng Zhang, Yanyun Qu, Lizhuang Ma, Zongze Wu, Yuan Xie, DaCheng Tao
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions.
no code implementations • 6 May 2022 • Jiaqi Gao, Jingqi Li, Hongming Shan, Yanyun Qu, James Z. Wang, Fei-Yue Wang, Junping Zhang
Crowd counting has important applications in public safety and pandemic control.
no code implementations • CVPR 2022 • Xia Kong, Zuodong Gao, Xiaofan Li, Ming Hong, Jun Liu, Chengjie Wang, Yuan Xie, Yanyun Qu
Our ICCE promotes intra-class compactness with inter-class separability on both seen and unseen classes in the embedding space and visual feature space.
2 code implementations • ACM 2021 • Xiaotong Luo, Qiuyuan Liang, Ding Liu, Yanyun Qu
The joint-distillation learning consists of internal self-distillation and external mutual learning.
9 code implementations • 25 May 2021 • Yanbo Wang, Shaohui Lin, Yanyun Qu, Haiyan Wu, Zhizhong Zhang, Yuan Xie, Angela Yao
Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead, significantly restricts their practical deployments on resource-limited devices.
2 code implementations • CVPR 2021 • Jingyu Gong, Jiachen Xu, Xin Tan, Haichuan Song, Yanyun Qu, Yuan Xie, Lizhuang Ma
Our method can significantly improve the backbones in all three datasets.
Ranked #2 on
Semantic Segmentation
on Semantic3D
10 code implementations • CVPR 2021 • Haiyan Wu, Yanyun Qu, Shaohui Lin, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie, Lizhuang Ma
In this paper, we propose a novel contrastive regularization (CR) built upon contrastive learning to exploit both the information of hazy images and clear images as negative and positive samples, respectively.
Ranked #5 on
Image Dehazing
on RS-Haze
4 code implementations • CVPR 2021 • Xudong Tian, Zhizhong Zhang, Shaohui Lin, Yanyun Qu, Yuan Xie, Lizhuang Ma
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing the redundancy.
Cross-Modality Person Re-identification
Cross-Modal Person Re-Identification
+3
no code implementations • Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence 2021 • Xuncheng Liu, Xudong Tian, Shaohui Lin, Yanyun Qu, Lizhuang Ma, Wang Yuan, Zhizhong Zhang, Yuan Xie
In this paper, we present a novel purified memory mechanism that simulates the recognition process of human beings.
no code implementations • 7 Jan 2021 • Jingyu Gong, Jiachen Xu, Xin Tan, Jie zhou, Yanyun Qu, Yuan Xie, Lizhuang Ma
Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in feature extraction, leading to misclassification in the transition area between two objects.
3 code implementations • ICCV 2021 • Yachao Zhang, Yanyun Qu, Yuan Xie, Zonghao Li, Shanshan Zheng, Cuihua Li
In this way, the graph topology of the whole point cloud can be effectively established by the introduced auxiliary supervision, such that the information propagation between the labeled and unlabeled points will be realized.
3 code implementations • 15 Sep 2020 • Kai Zhang, Martin Danelljan, Yawei Li, Radu Timofte, Jie Liu, Jie Tang, Gangshan Wu, Yu Zhu, Xiangyu He, Wenjie Xu, Chenghua Li, Cong Leng, Jian Cheng, Guangyang Wu, Wenyi Wang, Xiaohong Liu, Hengyuan Zhao, Xiangtao Kong, Jingwen He, Yu Qiao, Chao Dong, Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan, Xiaochuan Li, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Abdul Muqeet, Jiwon Hwang, Subin Yang, JungHeum Kang, Sung-Ho Bae, Yongwoo Kim, Geun-Woo Jeon, Jun-Ho Choi, Jun-Hyuk Kim, Jong-Seok Lee, Steven Marty, Eric Marty, Dongliang Xiong, Siang Chen, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Haicheng Wang, Vineeth Bhaskara, Alex Levinshtein, Stavros Tsogkas, Allan Jepson, Xiangzhen Kong, Tongtong Zhao, Shanshan Zhao, Hrishikesh P. S, Densen Puthussery, Jiji C. V, Nan Nan, Shuai Liu, Jie Cai, Zibo Meng, Jiaming Ding, Chiu Man Ho, Xuehui Wang, Qiong Yan, Yuzhi Zhao, Long Chen, Jiangtao Zhang, Xiaotong Luo, Liang Chen, Yanyun Qu, Long Sun, Wenhao Wang, Zhenbing Liu, Rushi Lan, Rao Muhammad Umer, Christian Micheloni
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
no code implementations • 7 May 2020 • Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu, Radu Timofte, Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma, Ziling Huang, Qili Deng, Ju-Chin Chao, Tsung-Shan Yang, Peng-Wen Chen, Po-Min Hsu, Tzu-Yi Liao, Chung-En Sun, Pei-Yuan Wu, Jeonghyeok Do, Jongmin Park, Munchurl Kim, Kareem Metwaly, Xuelu Li, Tiantong Guo, Vishal Monga, Mingzhao Yu, Venkateswararao Cherukuri, Shiue-Yuan Chuang, Tsung-Nan Lin, David Lee, Jerome Chang, Zhan-Han Wang, Yu-Bang Chang, Chang-Hong Lin, Yu Dong, Hong-Yu Zhou, Xiangzhen Kong, Sourya Dipta Das, Saikat Dutta, Xuan Zhao, Bing Ouyang, Dennis Estrada, Meiqi Wang, Tianqi Su, Siyi Chen, Bangyong Sun, Vincent Whannou de Dravo, Zhe Yu, Pratik Narang, Aryan Mehra, Navaneeth Raghunath, Murari Mandal
We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze free and nonhomogeneous hazy images recorded outdoor.
no code implementations • 6 May 2020 • Shanxin Yuan, Radu Timofte, Ales Leonardis, Gregory Slabaugh, Xiaotong Luo, Jiangtao Zhang, Yanyun Qu, Ming Hong, Yuan Xie, Cuihua Li, Dejia Xu, Yihao Chu, Qingyan Sun, Shuai Liu, Ziyao Zong, Nan Nan, Chenghua Li, Sangmin Kim, Hyungjoon Nam, Jisu Kim, Jechang Jeong, Manri Cheon, Sung-Jun Yoon, Byungyeon Kang, Junwoo Lee, Bolun Zheng, Xiaohong Liu, Linhui Dai, Jun Chen, Xi Cheng, Zhen-Yong Fu, Jian Yang, Chul Lee, An Gia Vien, Hyunkook Park, Sabari Nathan, M. Parisa Beham, S Mohamed Mansoor Roomi, Florian Lemarchand, Maxime Pelcat, Erwan Nogues, Densen Puthussery, Hrishikesh P. S, Jiji C. V, Ashish Sinha, Xuan Zhao
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
no code implementations • 19 Feb 2020 • Tong Wu, Yuan Xie, Yanyun Qu, Bicheng Dai, Shuxin Chen
MSN can fast generate the weights of fusion layers through a simple meta-learner, requiring only a few training samples and epochs to converge.
no code implementations • 3 Feb 2020 • Chengwei Chen, Wang Yuan, Yuan Xie, Yanyun Qu, Yiqing Tao, Haichuan Song, Lizhuang Ma
One-class novelty detection is the process of determining if a query example differs from the training examples (the target class).
no code implementations • 8 Nov 2019 • Shanxin Yuan, Radu Timofte, Gregory Slabaugh, Ales Leonardis, Bolun Zheng, Xin Ye, Xiang Tian, Yaowu Chen, Xi Cheng, Zhen-Yong Fu, Jian Yang, Ming Hong, Wenying Lin, Wenjin Yang, Yanyun Qu, Hong-Kyu Shin, Joon-Yeon Kim, Sung-Jea Ko, Hang Dong, Yu Guo, Jie Wang, Xuan Ding, Zongyan Han, Sourya Dipta Das, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A. N. Rajagopalan
A new dataset, called LCDMoire was created for this challenge, and consists of 10, 200 synthetically generated image pairs (moire and clean ground truth).
1 code implementation • CVPR 2019 • Yanyun Qu, Yizi Chen, Jingying Huang, Yuan Xie
Inspired by visual perception global-first theory, the discriminator guides the generator to create a pseudo realistic image on a coarse scale, while the enhancer following the generator is required to produce a realistic dehazing image on the fine scale.
Ranked #29 on
Image Dehazing
on SOTS Indoor
no code implementations • 1 Nov 2018 • Xiaotong Luo, Rong Chen, Yuan Xie, Yanyun Qu, Cuihua Li
In this paper, motivated by [1], we aim to generate a high-quality SR result which balances between the two indices, i. e., the perception index and root-mean-square error (RMSE).
no code implementations • 19 Aug 2018 • Bingqian Lin, Yuan Xie, Yanyun Qu, Cuihua Li, Xiaodan Liang
To our best knowledge, this is the first work to model the multi-view clustering in a deep joint framework, which will provide a meaningful thinking in unsupervised multi-view learning.
no code implementations • 15 Sep 2017 • Yanyun Qu, Jinyan Liu, Yuan Xie, Wensheng Zhang
In particular, the original tensor-based multi-view self-representation clustering problem is a special case of our approach and can be solved by our algorithm.
no code implementations • 15 Sep 2017 • Yanyun Qu, Li Lin, Fumin Shen, Chang Lu, Yang Wu, Yuan Xie, DaCheng Tao
We propose a novel image classification method based on learning hierarchical inter-class structures.
no code implementations • 23 Oct 2016 • Yuan Xie, DaCheng Tao, Wensheng Zhang, Lei Zhang, Yan Liu, Yanyun Qu
Different from traditional unfolding based tensor norm, this low-rank tensor constraint has optimality properties similar to that of matrix rank derived from SVD, so the complementary information among views can be explored more efficiently and thoroughly.
no code implementations • 17 Jan 2014 • Yuan Xie, Wensheng Zhang, DaCheng Tao, Wenrui Hu, Yanyun Qu, Hanzi Wang
To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new variational model and distortion-driven spatial-temporal kernel regression.