Search Results for author: Yanwei Fu

Found 151 papers, 59 papers with code

dS^2LBI: Exploring Structural Sparsity on Deep Network via Differential Inclusion Paths

no code implementations ICML 2020 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

fMRI-PTE: A Large-scale fMRI Pretrained Transformer Encoder for Multi-Subject Brain Activity Decoding

no code implementations1 Nov 2023 Xuelin Qian, Yun Wang, Jingyang Huo, Jianfeng Feng, Yanwei Fu

The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics, and virtual reality.

Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation

1 code implementation ICCV 2023 Ke Fan, Jingshi Lei, Xuelin Qian, Miaopeng Yu, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu

Furthermore, we propose a multi-view fusion layer based temporal module which is equipped with a set of object slots and interacts with features from different views by attention mechanism to fulfill sufficient object representation completion.

Video Segmentation Video Semantic Segmentation

Doubly Robust Proximal Causal Learning for Continuous Treatments

no code implementations22 Sep 2023 Yong Wu, Yanwei Fu, Shouyan Wang, Xinwei Sun

To address these challenges, we propose a kernel-based DR estimator that can well handle continuous treatments.

Unsupervised Open-Vocabulary Object Localization in Videos

no code implementations ICCV 2023 Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He

In this paper, we show that recent advances in video representation learning and pre-trained vision-language models allow for substantial improvements in self-supervised video object localization.

Object Localization Representation Learning

Object-Centric Multiple Object Tracking

1 code implementation ICCV 2023 Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao

Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing the annotation burden of multiple-object tracking (MOT) pipelines.

Multiple Object Tracking object-detection +2

Coarse-to-Fine Amodal Segmentation with Shape Prior

no code implementations ICCV 2023 Jianxiong Gao, Xuelin Qian, Yikai Wang, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu

To address this issue, we propose a convolution refine module to inject fine-grained information and provide a more precise amodal object segmentation based on visual features and coarse-predicted segmentation.

Segmentation Semantic Segmentation

WALL-E: Embodied Robotic WAiter Load Lifting with Large Language Model

no code implementations30 Aug 2023 Tianyu Wang, YiFan Li, Haitao Lin, xiangyang xue, Yanwei Fu

The target instruction is then forwarded to a visual grounding system for object pose and size estimation, following which the robot grasps the object accordingly.

Language Modelling Large Language Model +2

Rethinking Person Re-identification from a Projection-on-Prototypes Perspective

no code implementations21 Aug 2023 Qizao Wang, Xuelin Qian, Bin Li, Yanwei Fu, xiangyang xue

In this paper, we rethink the role of the classifier in person Re-ID, and advocate a new perspective to conceive the classifier as a projection from image features to class prototypes.

Person Re-Identification Person Retrieval +1

Exploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification

no code implementations21 Aug 2023 Qizao Wang, Xuelin Qian, Bin Li, Ying Fu, Yanwei Fu, xiangyang xue

Images with similar so-called fine-grained attributes (e. g., clothes and viewpoints) are encouraged to cluster together.

Person Re-Identification

Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning

no code implementations6 Aug 2023 Linbo Wang, Jing Wu, Xianyong Fang, Zhengyi Liu, Chenjie Cao, Yanwei Fu

First, we propose a Local Feature Consensus (LFC) plugin block to augment the features of existing models.

Pushing the Limits of 3D Shape Generation at Scale

no code implementations20 Jun 2023 Yu Wang, Xuelin Qian, Jingyang Huo, Tiejun Huang, Bo Zhao, Yanwei Fu

Through the adaptation of the Auto-Regressive model and the utilization of large language models, we have developed a remarkable model with an astounding 3. 6 billion trainable parameters, establishing it as the largest 3D shape generation model to date, named Argus-3D.

3D Shape Generation Quantization +1

GeoVLN: Learning Geometry-Enhanced Visual Representation with Slot Attention for Vision-and-Language Navigation

1 code implementation CVPR 2023 Jingyang Huo, Qiang Sun, Boyan Jiang, Haitao Lin, Yanwei Fu

Technically, we introduce a two-stage module that combine local slot attention and CLIP model to produce geometry-enhanced representation from such input.

Vision and Language Navigation

Faster OreFSDet : A Lightweight and Effective Few-shot Object Detector for Ore Images

1 code implementation2 May 2023 Yang Zhang, Le Cheng, Yuting Peng, Chengming Xu, Yanwei Fu, Bo Wu, Guodong Sun

For the ore particle size detection, obtaining a sizable amount of high-quality ore labeled data is time-consuming and expensive.

object-detection Object Detection

Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions

1 code implementation CVPR 2023 Yun He, Danhang Tang, yinda zhang, xiangyang xue, Yanwei Fu

Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction.

Learning Versatile 3D Shape Generation with Improved AR Models

no code implementations26 Mar 2023 Simian Luo, Xuelin Qian, Yanwei Fu, yinda zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, xiangyang xue

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space.

3D Shape Generation Image Generation +1

Joint fMRI Decoding and Encoding with Latent Embedding Alignment

no code implementations26 Mar 2023 Xuelin Qian, Yikai Wang, Yanwei Fu, Xinwei Sun, xiangyang xue, Jianfeng Feng

Our Latent Embedding Alignment (LEA) model concurrently recovers visual stimuli from fMRI signals and predicts brain activity from images within a unified framework.

Image Generation

Rethinking the Multi-view Stereo from the Perspective of Rendering-based Augmentation

no code implementations11 Mar 2023 Chenjie Cao, Xinlin Ren, xiangyang xue, Yanwei Fu

To address these problems, we first apply one of the state-of-the-art learning-based MVS methods, --MVSFormer, to overcome intractable scenarios such as textureless and reflections regions suffered by traditional PatchMatch methods, but it fails in a few large scenes' reconstructions.

Improving Transformer-based Image Matching by Cascaded Capturing Spatially Informative Keypoints

1 code implementation ICCV 2023 Chenjie Cao, Yanwei Fu

Learning robust local image feature matching is a fundamental low-level vision task, which has been widely explored in the past few years.

Pose Estimation Visual Localization

Entity-Level Text-Guided Image Manipulation

no code implementations22 Feb 2023 Yikai Wang, Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Wei zhang, Yanwei Fu

In the image manipulation phase, SeMani adopts a generative model to synthesize new images conditioned on the entity-irrelevant regions and target text descriptions.

Denoising Image Manipulation

StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning

1 code implementation CVPR 2023 Yuqian Fu, Yu Xie, Yanwei Fu, Yu-Gang Jiang

Thus, inspired by vanilla adversarial learning, a novel model-agnostic meta Style Adversarial training (StyleAdv) method together with a novel style adversarial attack method is proposed for CD-FSL.

Adversarial Attack cross-domain few-shot learning

Exploring Efficient Few-shot Adaptation for Vision Transformers

1 code implementation6 Jan 2023 Chengming Xu, Siqian Yang, Yabiao Wang, Zhanxiong Wang, Yanwei Fu, xiangyang xue

Essentially, despite ViTs have been shown to enjoy comparable or even better performance on other vision tasks, it is still very nontrivial to efficiently finetune the ViTs in real-world FSL scenarios.

Few-Shot Learning

Vocabulary-informed Zero-shot and Open-set Learning

1 code implementation3 Jan 2023 Yanwei Fu, Xiaomei Wang, Hanze Dong, Yu-Gang Jiang, Meng Wang, xiangyang xue, Leonid Sigal

Despite significant progress in object categorization, in recent years, a number of important challenges remain; mainly, the ability to learn from limited labeled data and to recognize object classes within large, potentially open, set of labels.

Object Categorization Open Set Learning +1

Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels

1 code implementation2 Jan 2023 Yikai Wang, Yanwei Fu, Xinwei Sun

While Knockoffs-SPR can be regarded as a sample selection module for a standard supervised training pipeline, we further combine it with a semi-supervised algorithm to exploit the support of noisy data as unlabeled data.

Learning with noisy labels regression

Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning

1 code implementation30 Nov 2022 Chengming Xu, Chen Liu, Siqian Yang, Yabiao Wang, Shijie Zhang, Lijie Jia, Yanwei Fu

Since only part of the most confident positive samples are available and evidence is not enough to categorize the rest samples, many of these unlabeled data may also be the positive samples.

Binary Classification

PatchMix Augmentation to Identify Causal Features in Few-shot Learning

no code implementations29 Nov 2022 Chengming Xu, Chen Liu, Xinwei Sun, Siqian Yang, Yabiao Wang, Chengjie Wang, Yanwei Fu

We theoretically show that such an augmentation mechanism, different from existing ones, is able to identify the causal features.

Data Augmentation Few-Shot Learning +1

RankDNN: Learning to Rank for Few-shot Learning

1 code implementation28 Nov 2022 Qianyu Guo, Hongtong Gong, Xujun Wei, Yanwei Fu, Weifeng Ge, Yizhou Yu, Wenqiang Zhang

This paper introduces a new few-shot learning pipeline that casts relevance ranking for image retrieval as binary ranking relation classification.

Few-Shot Learning Image Classification +4

Self-supervised Amodal Video Object Segmentation

1 code implementation23 Oct 2022 Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang

The key intuition is that the occluded part of an object can be explained away if that part is visible in other frames, possibly deformed as long as the deformation can be reasonably learned.

Segmentation Self-Supervised Learning +4

ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors

2 code implementations12 Oct 2022 Chenjie Cao, Qiaole Dong, Yanwei Fu

Specifically, given one corrupt image, we present the Transformer Structure Restorer (TSR) module to restore holistic structural priors at low image resolution, which are further upsampled by Simple Structure Upsampler (SSU) module to higher image resolution.

Image Inpainting

ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning

1 code implementation11 Oct 2022 Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang

Concretely, to solve the data imbalance problem between the source data with sufficient examples and the auxiliary target data with limited examples, we build our model under the umbrella of multi-expert learning.

cross-domain few-shot learning Knowledge Distillation

Specialized Re-Ranking: A Novel Retrieval-Verification Framework for Cloth Changing Person Re-Identification

no code implementations7 Oct 2022 Renjie Zhang, Yu Fang, Huaxin Song, Fangbin Wan, Yanwei Fu, Hirokazu Kato, Yang Wu

Cloth changing person re-identification(Re-ID) can work under more complicated scenarios with higher security than normal Re-ID and biometric techniques and is therefore extremely valuable in applications.

Person Re-Identification Re-Ranking +1

LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling

1 code implementation18 Aug 2022 Boyan Jiang, Xinlin Ren, Mingsong Dou, xiangyang xue, Yanwei Fu, yinda zhang

Recent progress in 4D implicit representation focuses on globally controlling the shape and motion with low dimensional latent vectors, which is prone to missing surface details and accumulating tracking error.

3D Shape Modeling 4D reconstruction +1

MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth

2 code implementations4 Aug 2022 Chenjie Cao, Xinlin Ren, Yanwei Fu

In this paper, we propose a pre-trained ViT enhanced MVS network called MVSFormer, which can learn more reliable feature representations benefited by informative priors from ViT.

3D Reconstruction Point Clouds +1

Learning Prior Feature and Attention Enhanced Image Inpainting

1 code implementation3 Aug 2022 Chenjie Cao, Qiaole Dong, Yanwei Fu

To this end, this paper incorporates the pre-training based Masked AutoEncoder (MAE) into the inpainting model, which enjoys richer informative priors to enhance the inpainting process.

Image Inpainting Image Restoration +2

Vision Transformers: From Semantic Segmentation to Dense Prediction

1 code implementation19 Jul 2022 Li Zhang, Jiachen Lu, Sixiao Zheng, Xinxuan Zhao, Xiatian Zhu, Yanwei Fu, Tao Xiang, Jianfeng Feng, Philip H. S. Torr

In this work, for the first time we explore the global context learning potentials of ViTs for dense visual prediction (e. g., semantic segmentation).

Image Classification Instance Segmentation +5

RCLane: Relay Chain Prediction for Lane Detection

no code implementations19 Jul 2022 Shenghua Xu, Xinyue Cai, Bin Zhao, Li Zhang, Hang Xu, Yanwei Fu, xiangyang xue

This is because most of the existing lane detection methods either treat the lane detection as a dense prediction or a detection task, few of them consider the unique topologies (Y-shape, Fork-shape, nearly horizontal lane) of the lane markers, which leads to sub-optimal solution.

Lane Detection

Local Slot Attention for Vision-and-Language Navigation

1 code implementation17 Jun 2022 Yifeng Zhuang, Qiang Sun, Yanwei Fu, Lifeng Chen, xiangyang xue

Since the attention mechanism in the transformer architecture can better integrate inter- and intra-modal information of vision and language.

Navigate Vision and Language Navigation

Wavelet Prior Attention Learning in Axial Inpainting Network

no code implementations7 Jun 2022 Chenjie Cao, Chengrong Wang, Yuntao Zhang, Yanwei Fu

Image inpainting is the task of filling masked or unknown regions of an image with visually realistic contents, which has been remarkably improved by Deep Neural Networks (DNNs) recently.

Image Inpainting Semantic Segmentation

I Know What You Draw: Learning Grasp Detection Conditioned on a Few Freehand Sketches

no code implementations9 May 2022 Haitao Lin, Chilam Cheang, Yanwei Fu, xiangyang xue

The physical robot experiments confirm the utility of our method in object-cluttered scenes.

Learning 6-DoF Object Poses to Grasp Category-level Objects by Language Instructions

no code implementations9 May 2022 Chilam Cheang, Haitao Lin, Yanwei Fu, xiangyang xue

This paper studies the task of any objects grasping from the known categories by free-form language instructions.

Object Localization Robotic Grasping

Density-preserving Deep Point Cloud Compression

no code implementations CVPR 2022 Yun He, Xinlin Ren, Danhang Tang, yinda zhang, xiangyang xue, Yanwei Fu

To address this, we propose a novel deep point cloud compression method that preserves local density information.

Pixel2Mesh++: 3D Mesh Generation and Refinement from Multi-View Images

no code implementations21 Apr 2022 Chao Wen, yinda zhang, Chenjie Cao, Zhuwen Li, xiangyang xue, Yanwei Fu

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses.

ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation

no code implementations CVPR 2022 Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Chunjing Xu, Yanwei Fu

Existing text-guided image manipulation methods aim to modify the appearance of the image or to edit a few objects in a virtual or simple scenario, which is far from practical application.

Image Generation Image Manipulation

DST: Dynamic Substitute Training for Data-free Black-box Attack

no code implementations CVPR 2022 Wenxuan Wang, Xuelin Qian, Yanwei Fu, xiangyang xue

With the wide applications of deep neural network models in various computer vision tasks, more and more works study the model vulnerability to adversarial examples.

Knowledge Distillation

ImpDet: Exploring Implicit Fields for 3D Object Detection

no code implementations31 Mar 2022 Xuelin Qian, Li Wang, Yi Zhu, Li Zhang, Yanwei Fu, xiangyang xue

Conventional 3D object detection approaches concentrate on bounding boxes representation learning with several parameters, i. e., localization, dimension, and orientation.

3D Object Detection object-detection +1

A Framework of Meta Functional Learning for Regularising Knowledge Transfer

no code implementations28 Mar 2022 Pan Li, Yanwei Fu, Shaogang Gong

The MFL computes meta-knowledge on functional regularisation generalisable to different learning tasks by which functional training on limited labelled data promotes more discriminative functions to be learned.

cross-domain few-shot learning Transfer Learning

Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison

no code implementations27 Mar 2022 Tianying Liu, Lu Zhang, Yang Wang, Jihong Guan, Yanwei Fu, Jiajia Zhao, Shuigeng Zhou

To this end, the Few-Shot Object Detection (FSOD) has been topical recently, as it mimics the humans' ability of learning to learn, and intelligently transfers the learned generic object knowledge from the common heavy-tailed, to the novel long-tailed object classes.

Few-Shot Object Detection Meta-Learning +2

QS-Craft: Learning to Quantize, Scrabble and Craft for Conditional Human Motion Animation

no code implementations22 Mar 2022 Yuxin Hong, Xuelin Qian, Simian Luo, xiangyang xue, Yanwei Fu

To this end, this paper proposes a novel model of learning to Quantize, Scrabble, and Craft (QS-Craft) for conditional human motion animation.

Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning

no code implementations15 Mar 2022 Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang

The key challenge of CD-FSL lies in the huge data shift between source and target domains, which is typically in the form of totally different visual styles.

cross-domain few-shot learning Self-Supervised Learning

H4D: Human 4D Modeling by Learning Neural Compositional Representation

no code implementations CVPR 2022 Boyan Jiang, yinda zhang, Xingkui Wei, xiangyang xue, Yanwei Fu

A simple yet effective linear motion model is proposed to provide a rough and regularized motion estimation, followed by per-frame compensation for pose and geometry details with the residual encoded in the auxiliary code.

3D Reconstruction Future prediction +2

Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding

1 code implementation CVPR 2022 Qiaole Dong, Chenjie Cao, Yanwei Fu

The proposed model restores holistic image structures with a powerful attention-based transformer model in a fixed low-resolution sketch space.

Image Inpainting

Clustering by the Probability Distributions from Extreme Value Theory

1 code implementation20 Feb 2022 Sixiao Zheng, Ke Fan, Yanxi Hou, Jianfeng Feng, Yanwei Fu

In contrast, the GPD fits the distribution of distance to the centroid exceeding a sufficiently large threshold, leading to a more stable performance of GPD k-means.


Learning To Memorize Feature Hallucination for One-Shot Image Generation

no code implementations CVPR 2022 Yu Xie, Yanwei Fu, Ying Tai, Yun Cao, Junwei Zhu, Chengjie Wang

In this paper, we propose a novel model to explicitly learn and memorize reusable features that can help hallucinate novel category images.

Image Generation


no code implementations29 Sep 2021 Wang Tian Xiang, Meiyue Shao, Yanwei Fu, Riheng Jia, Feilong Lin, ZhongLong Zheng

Typically, aggregation rules are utilized to protect the model from the attacks in federated learning.

Federated Learning

An Improved Composite Functional Gradient Learning by Wasserstein Regularization for Generative adversarial networks

no code implementations29 Sep 2021 Chang Wan, Yanwei Fu, Ke Fan, Jinshan Zeng, Ming Zhong, Riheng Jia, MingLu Li, ZhongLong Zheng

However, the discriminator using logistic regression from the CFG framework is gradually hard to discriminate between real and fake images while the training steps go on.

Image Generation regression

Relative Instance Credibility Inference for Learning with Noisy Labels

no code implementations29 Sep 2021 Yikai Wang, Xinwei Sun, Yanwei Fu

Specifically, we re-purpose a sparse linear model with incidental parameters as a unified Relative Instance Credibility Inference (RICI) framework, which will detect and remove outliers in the forward pass of each mini-batch and use the remaining instances to train the network.

Learning with noisy labels

The Report on China-Spain Joint Clinical Testing for Rapid COVID-19 Risk Screening by Eye-region Manifestations

no code implementations18 Sep 2021 Yanwei Fu, Feng Li, Paula boned Fustel, Lei Zhao, Lijie Jia, Haojie Zheng, Qiang Sun, Shisong Rong, Haicheng Tang, xiangyang xue, Li Yang, Hong Li, Jiao Xie Wenxuan Wang, Yuan Li, Wei Wang, Yantao Pei, Jianmin Wang, Xiuqi Wu, Yanhua Zheng, Hongxia Tian, Mengwei Gu

The image-level performance of COVID-19 prescreening model in the China-Spain multicenter study achieved an AUC of 0. 913 (95% CI, 0. 898-0. 927), with a sensitivity of 0. 695 (95% CI, 0. 643-0. 748), a specificity of 0. 904 (95% CI, 0. 891 -0. 919), an accuracy of 0. 875(0. 861-0. 889), and a F1 of 0. 611(0. 568-0. 655).

Binary Classification Specificity

Deep Hybrid Self-Prior for Full 3D Mesh Generation

no code implementations ICCV 2021 Xingkui Wei, Zhengqing Chen, Yanwei Fu, Zhaopeng Cui, yinda zhang

We present a deep learning pipeline that leverages network self-prior to recover a full 3D model consisting of both a triangular mesh and a texture map from the colored 3D point cloud.

Surface Reconstruction

A Unified Efficient Pyramid Transformer for Semantic Segmentation

no code implementations29 Jul 2021 Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo wu, Yanwei Fu, Mu Li

Semantic segmentation is a challenging problem due to difficulties in modeling context in complex scenes and class confusions along boundaries.

Segmentation Semantic Segmentation

Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data

1 code implementation26 Jul 2021 Yuqian Fu, Yanwei Fu, Yu-Gang Jiang

Secondly, a novel disentangle module together with a domain classifier is proposed to extract the disentangled domain-irrelevant and domain-specific features.

cross-domain few-shot learning

Can Action be Imitated? Learn to Reconstruct and Transfer Human Dynamics from Videos

no code implementations25 Jul 2021 Yuqian Fu, Yanwei Fu, Yu-Gang Jiang

To achieve this, a novel Mesh-based Video Action Imitation (M-VAI) method is proposed by us.

Human Dynamics

SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimation

no code implementations CVPR 2022 Haitao Lin, Zichang Liu, Chilam Cheang, Yanwei Fu, Guodong Guo, xiangyang xue

The concatenation of the observed point cloud and symmetric one reconstructs a coarse object shape, thus facilitating object center (3D translation) and 3D size estimation.

Optical Character Recognition (OCR)

Rapid COVID-19 Risk Screening by Eye-region Manifestations

no code implementations12 Jun 2021 Yanwei Fu, Lei Zhao, Haojie Zheng, Qiang Sun, Li Yang, Hong Li, Jiao Xie, xiangyang xue, Feng Li, Yuan Li, Wei Wang, Yantao Pei, Jianmin Wang, Xiuqi Wu, Yanhua Zheng, Hongxia Tian Mengwei Gu1

It is still nontrivial to develop a new fast COVID-19 screening method with the easier access and lower cost, due to the technical and cost limitations of the current testing methods in the medical resource-poor districts.


The Image Local Autoregressive Transformer

1 code implementation NeurIPS 2021 Chenjie Cao, Yuxin Hong, Xiang Li, Chengrong Wang, Chengming Xu, xiangyang xue, Yanwei Fu

To address these limitations, we propose a novel model -- image Local Autoregressive Transformer (iLAT), to better facilitate the locally guided image synthesis.

Image Generation

NMS-Loss: Learning with Non-Maximum Suppression for Crowded Pedestrian Detection

1 code implementation4 Jun 2021 Zekun Luo, Zheng Fang, Sixiao Zheng, Yabiao Wang, Yanwei Fu

Non-Maximum Suppression (NMS) is essential for object detection and affects the evaluation results by incorporating False Positives (FP) and False Negatives (FN), especially in crowd occlusion scenes.

object-detection Object Detection +1

Delving into Data: Effectively Substitute Training for Black-box Attack

no code implementations CVPR 2021 Wenxuan Wang, Bangjie Yin, Taiping Yao, Li Zhang, Yanwei Fu, Shouhong Ding, Jilin Li, Feiyue Huang, xiangyang xue

Previous substitute training approaches focus on stealing the knowledge of the target model based on real training data or synthetic data, without exploring what kind of data can further improve the transferability between the substitute and target models.

Adversarial Attack

Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes

1 code implementation ICCV 2021 Chenjie Cao, Yanwei Fu

To this end, this paper proposes learning a Sketch Tensor (ST) space for inpainting man-made scenes.

Image Inpainting

Learning Dynamic Alignment via Meta-filter for Few-shot Learning

1 code implementation CVPR 2021 Chengming Xu, Chen Liu, Li Zhang, Chengjie Wang, Jilin Li, Feiyue Huang, xiangyang xue, Yanwei Fu

Our insight is that these methods would lead to poor adaptation with redundant matching, and leveraging channel-wise adjustment is the key to well adapting the learned knowledge to new classes.

Few-Shot Learning

Incrementally Zero-Shot Detection by an Extreme Value Analyzer

no code implementations23 Mar 2021 Sixiao Zheng, Yanwei Fu, Yanxi Hou

However, zero-shot learning models assume that all seen classes should be known beforehand, while incremental learning models cannot recognize unseen classes.

Class Incremental Learning Incremental Learning +3

Learning Compositional Representation for 4D Captures with Neural ODE

no code implementations CVPR 2021 Boyan Jiang, yinda zhang, Xingkui Wei, xiangyang xue, Yanwei Fu

To model the motion, a neural Ordinary Differential Equation (ODE) is trained to update the initial state conditioned on the learned motion code, and a decoder takes the shape code and the updated state code to reconstruct the 3D model at each time stamp.

4D reconstruction

A Simple Feature Augmentation for Domain Generalization

no code implementations ICCV 2021 Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales

The topical domain generalization (DG) problem asks trained models to perform well on an unseen target domain with different data statistics from the source training domains.

Data Augmentation Domain Generalization

Whose hand is this? Person Identification from Egocentric Hand Gestures

no code implementations17 Nov 2020 Satoshi Tsutsui, Yanwei Fu, David Crandall

But while one's own face is not frequently visible, their hands are: in fact, hands are among the most common objects in one's own field of view.

Gesture Recognition Person Identification

Data-efficient Alignment of Multimodal Sequences by Aligning Gradient Updates and Internal Feature Distributions

1 code implementation15 Nov 2020 Jianan Wang, Boyang Li, Xiangyu Fan, Jing Lin, Yanwei Fu

The task of video and text sequence alignment is a prerequisite step toward joint understanding of movie videos and screenplays.

Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition

1 code implementation20 Oct 2020 Yuqian Fu, Li Zhang, Junke Wang, Yanwei Fu, Yu-Gang Jiang

Humans can easily recognize actions with only a few examples given, while the existing video recognition models still heavily rely on the large-scale labeled data inputs.

Few Shot Action Recognition Meta-Learning +2

M3Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening from CT Imaging

no code implementations7 Oct 2020 Xuelin Qian, Huazhu Fu, Weiya Shi, Tao Chen, Yanwei Fu, Fei Shan, xiangyang xue

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic.

A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools

no code implementations4 Sep 2020 Yanwei Fu, Feng Li, Wenxuan Wang, Haicheng Tang, Xuelin Qian, Mengwei Gu, xiangyang xue

After more than four months study, we found that the confirmed cases of COVID-19 present the consistent ocular pathological symbols; and we propose a new screening method of analyzing the eye-region images, captured by common CCD and CMOS cameras, could reliably make a rapid risk screening of COVID-19 with very high accuracy.

BIG-bench Machine Learning Ethics +2

Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

1 code implementation ECCV 2020 Jinlong Peng, Changan Wang, Fangbin Wan, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yanwei Fu

Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or have two of the three subtasks integrated to form a partially end-to-end solution.

Multiple Object Tracking object-detection +2

How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning

2 code implementations15 Jul 2020 Yikai Wang, Li Zhang, Yuan YAO, Yanwei Fu

We rank the credibility of pseudo-labeled instances along the regularization path of their corresponding incidental parameters, and the most trustworthy pseudo-labeled examples are preserved as the augmented labeled instances.

Data Augmentation Few-Shot Learning

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths

1 code implementation4 Jul 2020 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

Self-supervised Video Object Segmentation

no code implementations22 Jun 2020 Fangrui Zhu, Li Zhang, Yanwei Fu, Guodong Guo, Weidi Xie

The objective of this paper is self-supervised representation learning, with the goal of solving semi-supervised video object segmentation (a. k. a.

One-shot visual object segmentation Representation Learning +3

Long-Term Cloth-Changing Person Re-identification

no code implementations26 May 2020 Xuelin Qian, Wenxuan Wang, Li Zhang, Fangrui Zhu, Yanwei Fu, Tao Xiang, Yu-Gang Jiang, xiangyang xue

Specifically, we consider that under cloth-changes, soft-biometrics such as body shape would be more reliable.

Person Re-Identification

Sketch-BERT: Learning Sketch Bidirectional Encoder Representation from Transformers by Self-supervised Learning of Sketch Gestalt

1 code implementation CVPR 2020 Hangyu Lin, Yanwei Fu, Yu-Gang Jiang, xiangyang xue

Unfortunately, the representation learned by SketchRNN is primarily for the generation tasks, rather than the other tasks of recognition and retrieval of sketches.

Retrieval Self-Supervised Learning +1

Instance Credibility Inference for Few-Shot Learning

1 code implementation CVPR 2020 Yikai Wang, Chengming Xu, Chen Liu, Li Zhang, Yanwei Fu

To measure the credibility of each pseudo-labeled instance, we then propose to solve another linear regression hypothesis by increasing the sparsity of the incidental parameters and rank the pseudo-labeled instances with their sparsity degree.

Data Augmentation Few-Shot Image Classification +2

When Person Re-identification Meets Changing Clothes

no code implementations9 Mar 2020 Fangbin Wan, Yang Wu, Xuelin Qian, Yixiong Chen, Yanwei Fu

We find that changing clothes makes ReID a much harder problem in the sense of bringing difficulties to learning effective representations and also challenges the generalization ability of previous ReID models to identify persons with unseen (new) clothes.

Person Re-Identification Person Search

Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition

no code implementations17 Jan 2020 Wenxuan Wang, Yanwei Fu, Qiang Sun, Tao Chen, Chenjie Cao, Ziqi Zheng, Guoqiang Xu, Han Qiu, Yu-Gang Jiang, xiangyang xue

Considering the phenomenon of uneven data distribution and lack of samples is common in real-world scenarios, we further evaluate several tasks of few-shot expression learning by virtue of our F2ED, which are to recognize the facial expressions given only few training instances.

Facial Expression Recognition Facial Expression Recognition (FER)

DeepSFM: Structure From Motion Via Deep Bundle Adjustment

1 code implementation ECCV 2020 Xingkui Wei, yinda zhang, Zhuwen Li, Yanwei Fu, xiangyang xue

The explicit constraints on both depth (structure) and pose (motion), when combined with the learning components, bring the merit from both traditional BA and emerging deep learning technology.

Pose Estimation

Extreme Value k-means Clustering

no code implementations25 Sep 2019 Sixiao Zheng, Yanxi Hou, Yanwei Fu, Jianfeng Feng

We thus propose a novel algorithm called Extreme Value k-means (EV k-means), including GEV k-means and GPD k-means.


Split LBI for Deep Learning: Structural Sparsity via Differential Inclusion Paths

no code implementations25 Sep 2019 Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO

Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.

DeepEnFM: Deep neural networks with Encoder enhanced Factorization Machine

no code implementations25 Sep 2019 Qiang Sun, Zhinan Cheng, Yanwei Fu, Wenxuan Wang, Yu-Gang Jiang, xiangyang xue

Instead of learning the cross features directly, DeepEnFM adopts the Transformer encoder as a backbone to align the feature embeddings with the clues of other fields.

Click-Through Rate Prediction

Boosting Network: Learn by Growing Filters and Layers via SplitLBI

no code implementations25 Sep 2019 Zuyuan Zhong, Chen Liu, Yanwei Fu, Yuan YAO

Network structures are important to learning good representations of many tasks in computer vision and machine learning communities.

Neural Architecture Search

Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation

2 code implementations ICCV 2019 Chao Wen, yinda zhang, Zhuwen Li, Yanwei Fu

We study the problem of shape generation in 3D mesh representation from a few color images with known camera poses.

Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces

1 code implementation23 May 2019 Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, Yuan YAO

To fill in this gap, this paper proposes a new approach based on differential inclusions of inverse scale spaces, which generate a family of models from simple to complex ones along the dynamics via coupling a pair of parameters, such that over-parameterized deep models and their structural sparsity can be explored simultaneously.

$S^{2}$-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning

no code implementations24 Apr 2019 Yanwei Fu, Donghao Li, Xinwei Sun, Shun Zhang, Yizhou Wang, Yuan YAO

This paper proposes a novel Stochastic Split Linearized Bregman Iteration ($S^{2}$-LBI) algorithm to efficiently train the deep network.

Model Selection

Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin Softmax

1 code implementation11 Dec 2018 Peng Lu, Gao Huang, Hangyu Lin, Wenming Yang, Guodong Guo, Yanwei Fu

This paper proposes a novel approach for Sketch-Based Image Retrieval (SBIR), for which the key is to bridge the gap between sketches and photos in terms of the data representation.

Retrieval Sketch-Based Image Retrieval

Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning

1 code implementation NeurIPS 2018 Yunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei (Mark) Zhang

Zero-Shot Learning (ZSL) is generally achieved via aligning the semantic relationships between the visual features and the corresponding class semantic descriptions.

General Classification Multi-class Classification +2

Instance-level Sketch-based Retrieval by Deep Triplet Classification Siamese Network

no code implementations28 Nov 2018 Peng Lu, Hangyu Lin, Yanwei Fu, Shaogang Gong, Yu-Gang Jiang, xiangyang xue

Additionally, to study the tasks of sketch-based hairstyle retrieval, this paper contributes a new instance-level photo-sketch dataset - Hairstyle Photo-Sketch dataset, which is composed of 3600 sketches and photos, and 2400 sketch-photo pairs.

General Classification Retrieval +2

Learning the Compositional Spaces for Generalized Zero-shot Learning

no code implementations ICLR 2019 Hanze Dong, Yanwei Fu, Sung Ju Hwang, Leonid Sigal, xiangyang xue

This paper studies the problem of Generalized Zero-shot Learning (G-ZSL), whose goal is to classify instances belonging to both seen and unseen classes at the test time.

Generalized Zero-Shot Learning Open Set Learning +1


no code implementations27 Sep 2018 Qiang Sun, Bin Wang, Zizhou Gu, Yanwei Fu

The most used recommendation method is collaborative filtering, and the key part of collaborative filtering is to compute the similarity.

Collaborative Filtering Recommendation Systems

Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks

2 code implementations22 Aug 2018 Yang He, Xuanyi Dong, Guoliang Kang, Yanwei Fu, Chenggang Yan, Yi Yang

With asymptotic pruning, the information of the training set would be gradually concentrated in the remaining filters, so the subsequent training and pruning process would be stable.

Image Classification

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

6 code implementations21 Aug 2018 Yang He, Guoliang Kang, Xuanyi Dong, Yanwei Fu, Yi Yang

Therefore, the network trained by our method has a larger model capacity to learn from the training data.

Detecting Tiny Moving Vehicles in Satellite Videos

no code implementations5 Jul 2018 Wei Ao, Yanwei Fu, Feng Xu

Even worse, the noise signals also existed in the video frames, since the background of the video frame has the subpixel-level and uneven moving thanks to the motion of satellites.


SCSP: Spectral Clustering Filter Pruning with Soft Self-adaption Manners

no code implementations14 Jun 2018 Huiyuan Zhuo, Xuelin Qian, Yanwei Fu, Heng Yang, xiangyang xue

In this paper, we proposed a novel filter pruning for convolutional neural networks compression, namely spectral clustering filter pruning with soft self-adaption manners (SCSP).

Clustering Model Compression

MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning

no code implementations ICML 2018 Bo Zhao, Xinwei Sun, Yanwei Fu, Yuan YAO, Yizhou Wang

To solve this task, $L_{1}$ regularization is widely used for the pursuit of feature selection and avoiding overfitting, and yet the sparse estimation of features in $L_{1}$ regularization may cause the underfitting of training data.

feature selection Zero-Shot Learning

Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot Learning

no code implementations21 May 2018 Yunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei Zhang

To this end, we propose a novel stacked semantics-guided attention (S2GA) model to obtain semantic relevant features by using individual class semantic features to progressively guide the visual features to generate an attention map for weighting the importance of different local regions.

General Classification Multi-class Classification +2

Multi-level Semantic Feature Augmentation for One-shot Learning

1 code implementation15 Apr 2018 Zitian Chen, Yanwei Fu, yinda zhang, Yu-Gang Jiang, xiangyang xue, Leonid Sigal

In semantic space, we search for related concepts, which are then projected back into the image feature spaces by the decoder portion of the TriNet.

Novel Concepts One-Shot Learning

A Large-scale Attribute Dataset for Zero-shot Learning

1 code implementation12 Apr 2018 Bo Zhao, Yanwei Fu, Rui Liang, Jia-Hong Wu, Yonggang Wang, Yizhou Wang

In classical ZSL algorithms, attributes are introduced as the intermediate semantic representation to realize the knowledge transfer from seen classes to unseen classes.

Transfer Learning Zero-Shot Learning

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

6 code implementations ECCV 2018 Nanyang Wang, yinda zhang, Zhuwen Li, Yanwei Fu, Wei Liu, Yu-Gang Jiang

We propose an end-to-end deep learning architecture that produces a 3D shape in triangular mesh from a single color image.

3D Object Reconstruction

Learning to score the figure skating sports videos

1 code implementation8 Feb 2018 Chengming Xu, Yanwei Fu, Bing Zhang, Zitian Chen, Yu-Gang Jiang, xiangyang xue

This paper targets at learning to score the figure skating sports videos.


no code implementations ICLR 2018 jianqi ma, Hangyu Lin, yinda zhang, Yanwei Fu, xiangyang xue

Besides directly augmenting image features, we transform the image features to semantic space using the encoder and perform the data augmentation.

Classification Data Augmentation +2

Pose-Normalized Image Generation for Person Re-identification

2 code implementations ECCV 2018 Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, xiangyang xue

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations.

Image Generation Person Re-Identification +1

Dual Skipping Networks

no code implementations CVPR 2018 Changmao Cheng, Yanwei Fu, Yu-Gang Jiang, Wei Liu, Wenlian Lu, Jianfeng Feng, xiangyang xue

Inspired by the recent neuroscience studies on the left-right asymmetry of the human brain in processing low and high spatial frequency information, this paper introduces a dual skipping network which carries out coarse-to-fine object categorization.

General Classification Object Categorization

Recent Advances in Zero-shot Recognition

no code implementations13 Oct 2017 Yanwei Fu, Tao Xiang, Yu-Gang Jiang, xiangyang xue, Leonid Sigal, Shaogang Gong

With the recent renaissance of deep convolution neural networks, encouraging breakthroughs have been achieved on the supervised recognition tasks, where each class has sufficient training data and fully annotated training data.

Open Set Learning Zero-Shot Learning

Multi-scale Deep Learning Architectures for Person Re-identification

no code implementations ICCV 2017 Xuelin Qian, Yanwei Fu, Yu-Gang Jiang, Tao Xiang, xiangyang xue

Our model is able to learn deep discriminative feature representations at different scales and automatically determine the most suitable scales for matching.

Person Re-Identification

A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild

no code implementations27 Jul 2017 Keke He, Yanwei Fu, xiangyang xue

Facial attribute analysis in the real world scenario is very challenging mainly because of complex face variations.

Face Detection

Vocabulary-informed Extreme Value Learning

no code implementations28 May 2017 Yanwei Fu, Hanze Dong, Yu-feng Ma, Zhengjun Zhang, xiangyang xue

To solve this problem, we propose the Extreme Value Learning (EVL) formulation to learn the mapping from visual feature to semantic space.

Open Set Learning

Semi-Latent GAN: Learning to generate and modify facial images from attributes

no code implementations7 Apr 2017 Weidong Yin, Yanwei Fu, Leonid Sigal, xiangyang xue

Generating and manipulating human facial images using high-level attributal controls are important and interesting problems.

Learning to Generate Posters of Scientific Papers by Probabilistic Graphical Models

no code implementations21 Feb 2017 Yu-ting Qiang, Yanwei Fu, Xiao Yu, Yanwen Guo, Zhi-Hua Zhou, Leonid Sigal

In order to bridge the gap between panel attributes and the composition within each panel, we also propose a recursive page splitting algorithm to generate the panel layout for a poster.

Deep Learning for Video Classification and Captioning

1 code implementation22 Sep 2016 Zuxuan Wu, Ting Yao, Yanwei Fu, Yu-Gang Jiang

Accelerated by the tremendous increase in Internet bandwidth and storage space, video data has been generated, published and spread explosively, becoming an indispensable part of today's big data.

Classification General Classification +2

Semi-supervised Vocabulary-informed Learning

no code implementations CVPR 2016 Yanwei Fu, Leonid Sigal

Despite significant progress in object categorization, in recent years, a number of important challenges remain, mainly, ability to learn from limited labeled data and ability to recognize object classes within large, potentially open, set of labels.

Object Categorization Open Set Learning +1

Learning to Generate Posters of Scientific Papers

no code implementations5 Apr 2016 Yu-ting Qiang, Yanwei Fu, Yanwen Guo, Zhi-Hua Zhou, Leonid Sigal

Then, given inferred layout and attributes, composition of graphical elements within each panel is synthesized.

Robust Classification by Pre-conditioned LASSO and Transductive Diffusion Component Analysis

no code implementations19 Nov 2015 Yanwei Fu, De-An Huang, Leonid Sigal

Collecting datasets in this way, however, requires robust and efficient ways for detecting and excluding outliers that are common and prevalent.

BIG-bench Machine Learning Classification +3

Learning from Synthetic Data Using a Stacked Multichannel Autoencoder

no code implementations17 Sep 2015 Xi Zhang, Yanwei Fu, Shanshan Jiang, Leonid Sigal, Gady Agam

In this paper, we investigate and formalize a general framework-Stacked Multichannel Autoencoder (SMCAE) that enables bridging the synthetic gap and learning from synthetic data more efficiently.

Sketch Recognition

Transductive Multi-label Zero-shot Learning

no code implementations26 Mar 2015 Yanwei Fu, Yongxin Yang, Tim Hospedales, Tao Xiang, Shaogang Gong

Zero-shot learning has received increasing interest as a means to alleviate the often prohibitive expense of annotating training data for large scale recognition problems.

Multi-label zero-shot learning regression +2

Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder

no code implementations11 Mar 2015 Xi Zhang, Yanwei Fu, Andi Zang, Leonid Sigal, Gady Agam

Experimental results on two datasets validate the efficiency of our MCAE model and our methodology of generating synthetic data.

General Classification

Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels

no code implementations25 Jan 2015 Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong, Shaogang Gong, Yizhou Wang, Yuan YAO

In this paper, we propose a more principled way to identify annotation outliers by formulating the subjective visual property prediction task as a unified robust learning to rank problem, tackling both the outlier detection and learning to rank jointly.

Learning-To-Rank Outlier Detection +1

Transductive Multi-view Zero-Shot Learning

no code implementations19 Jan 2015 Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong

A projection from a low-level feature space to the semantic representation space is learned from the auxiliary dataset and is applied without adaptation to the target dataset.

Transfer Learning Zero-Shot Learning

Multi-view Metric Learning for Multi-view Video Summarization

no code implementations25 May 2014 Yanwei Fu, Lingbo Wang, Yanwen Guo

Traditional methods on video summarization are designed to generate summaries for single-view video records; and thus they cannot fully exploit the redundancy in multi-view video records.

Clustering Metric Learning +1

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