Search Results for author: Yanyun Qu

Found 42 papers, 15 papers with code

LatticeNet: Towards Lightweight Image Super-resolution with Lattice Block

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.

Image Super-Resolution

Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception

1 code implementation12 May 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.

object-detection Object Detection +2

Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification

no code implementations9 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.

Person Re-Identification Pseudo Label +1

PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection

2 code implementations8 Apr 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.

Anomaly Detection Language Modelling +1

Multi-Memory Matching for Unsupervised Visible-Infrared Person Re-Identification

no code implementations12 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.

Clustering Person Re-Identification +1

CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data

1 code implementation14 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.

Contrastive Learning Federated Learning +4

Beyond the Label Itself: Latent Labels Enhance Semi-supervised Point Cloud Panoptic Segmentation

no code implementations13 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.

Panoptic Segmentation Position

COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction

1 code implementation4 Dec 2023 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.

Autonomous Driving Decoder +1

Multi-Centroid Task Descriptor for Dynamic Class Incremental Inference

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.

Class Incremental Learning Incremental Learning

Efficient Converted Spiking Neural Network for 3D and 2D Classification

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.

Image Classification Point Cloud Classification

Dual Pseudo-Labels Interactive Self-Training for Semi-Supervised Visible-Infrared Person Re-Identification

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.

Person Re-Identification Pseudo Label

Memory-Friendly Scalable Super-Resolution via Rewinding Lottery Ticket Hypothesis

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.

Image Classification Model Compression +1

Rethinking Gradient Projection Continual Learning: Stability / Plasticity Feature Space Decoupling

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.

Continual Learning

Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud

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.

Colorization Pseudo Label +3

Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning

no code implementations16 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.

3D Semantic Segmentation Pseudo Label +2

Variational Distillation for Multi-View Learning

3 code implementations20 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.

MULTI-VIEW LEARNING Representation Learning

En-Compactness: Self-Distillation Embedding & Contrastive Generation for Generalized Zero-Shot Learning

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.

Generalized Zero-Shot Learning

Towards Compact Single Image Super-Resolution via Contrastive Self-distillation

8 code implementations25 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.

Image Super-Resolution SSIM +1

Contrastive Learning for Compact Single Image Dehazing

7 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.

Contrastive Learning Image Dehazing +1

Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification

3 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

Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds

no code implementations7 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.

Image Segmentation Point Cloud Segmentation +2

Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation

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.

Self-Supervised Learning Semantic Segmentation +1

Meta Segmentation Network for Ultra-Resolution Medical Images

no code implementations19 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.

Image Segmentation Meta-Learning +2

Novelty Detection via Non-Adversarial Generative Network

no code implementations3 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).

Decoder Image Reconstruction +1

Enhanced Pix2pix Dehazing Network

no code implementations 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.

Generative Adversarial Network Image Dehazing +3

Bi-GANs-ST for Perceptual Image Super-resolution

no code implementations1 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).

Image Super-Resolution SSIM

Jointly Deep Multi-View Learning for Clustering Analysis

no code implementations19 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.

Clustering Multiview Clustering +1

Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization

no code implementations15 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.

Clustering Face Clustering

On Unifying Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization

no code implementations23 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.

Clustering Multi-view Subspace Clustering

Distortion-driven Turbulence Effect Removal using Variational Model

no code implementations17 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.

regression

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