Search Results for author: Yunchao Wei

Found 86 papers, 40 papers with code

Content-Consistent Matching for Domain Adaptive Semantic Segmentation

1 code implementation ECCV 2020 Guangrui Li, Guoliang Kang, Wu Liu, Yunchao Wei, Yi Yang

The target of CCM is to acquire those synthetic images that share similar distribution with the real ones in the target domain, so that the domain gap can be naturally alleviated by employing the content-consistent synthetic images for training.

Domain Adaptation Semantic Segmentation +1

Cylin-Painting: Seamless 360° Panoramic Image Outpainting and Beyond with Cylinder-Style Convolutions

1 code implementation18 Apr 2022 Kang Liao, Xiangyu Xu, Chunyu Lin, Wenqi Ren, Yunchao Wei, Yao Zhao

Motivated by this analysis, we present a Cylin-Painting framework that involves meaningful collaborations between inpainting and outpainting and efficiently fuses the different arrangements, with a view to leveraging their complementary benefits on a consistent and seamless cylinder.

Depth Estimation Image Outpainting +2

L2G: A Simple Local-to-Global Knowledge Transfer Framework for Weakly Supervised Semantic Segmentation

1 code implementation7 Apr 2022 Peng-Tao Jiang, YuQi Yang, Qibin Hou, Yunchao Wei

Our framework conducts the global network to learn the captured rich object detail knowledge from a global view and thereby produces high-quality attention maps that can be directly used as pseudo annotations for semantic segmentation networks.

Transfer Learning Weakly-Supervised Semantic Segmentation

Associating Objects with Scalable Transformers for Video Object Segmentation

2 code implementations22 Mar 2022 Zongxin Yang, Jiaxu Miao, Xiaohan Wang, Yunchao Wei, Yi Yang

The state-of-the-art methods learn to decode features with a single positive object and thus have to match and segment each target separately under multi-object scenarios, consuming multiple times computation resources.

Semantic Segmentation Semi-Supervised Video Object Segmentation +1

Clicking Matters:Towards Interactive Human Parsing

no code implementations11 Nov 2021 Yutong Gao, Liqian Liang, Congyan Lang, Songhe Feng, Yidong Li, Yunchao Wei

In this work, we focus on Interactive Human Parsing (IHP), which aims to segment a human image into multiple human body parts with guidance from users' interactions.

Human Parsing Semantic Segmentation

M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining

no code implementations9 Sep 2021 Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, Michael C. Kampffmeyer, XiaoYong Wei, Minlong Lu, YaoWei Wang, Xiaodan Liang

Despite the potential of multi-modal pre-training to learn highly discriminative feature representations from complementary data modalities, current progress is being slowed by the lack of large-scale modality-diverse datasets.

Contrastive Learning

Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics

1 code implementation26 Aug 2021 Wuyang Chen, Xinyu Gong, Yunchao Wei, Humphrey Shi, Zhicheng Yan, Yi Yang, Zhangyang Wang

This work targets designing a principled and unified training-free framework for Neural Architecture Search (NAS), with high performance, low cost, and in-depth interpretation.

Neural Architecture Search

Generating Superpixels for High-resolution Images with Decoupled Patch Calibration

no code implementations19 Aug 2021 Yaxiong Wang, Yunchao Wei, Xueming Qian, Li Zhu, Yi Yang

Superpixel segmentation has recently seen important progress benefiting from the advances in differentiable deep learning.


Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining

1 code implementation ICCV 2021 Xunlin Zhan, Yangxin Wu, Xiao Dong, Yunchao Wei, Minlong Lu, Yichi Zhang, Hang Xu, Xiaodan Liang

In this paper, we investigate a more realistic setting that aims to perform weakly-supervised multi-modal instance-level product retrieval among fine-grained product categories.

LayerCAM: Exploring Hierarchical Class Activation Maps for Localization

2 code implementations IEEE 2021 Peng-Tao Jiang, Chang-Bin Zhang, Qibin Hou, Ming-Ming Cheng, Yunchao Wei

To evaluate the quality of the class activation maps produced by LayerCAM, we apply them to weakly-supervised object localization and semantic segmentation.

Semantic Segmentation Weakly-Supervised Object Localization

ReGO: Reference-Guided Outpainting for Scenery Image

no code implementations20 Jun 2021 Yaxiong Wang, Yunchao Wei, Xueming Qian, Li Zhu, Yi Yang

We aim to tackle the challenging yet practical scenery image outpainting task in this work.

Image Outpainting

Automated Deepfake Detection

no code implementations20 Jun 2021 Ping Liu, Yuewei Lin, Yang He, Yunchao Wei, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh, Jingen Liu

In this paper, we propose to utilize Automated Machine Learning to adaptively search a neural architecture for deepfake detection.

DeepFake Detection Face Swapping

VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild

no code implementations CVPR 2021 Jiaxu Miao, Yunchao Wei, Yu Wu, Chen Liang, Guangrui Li, Yi Yang

To the best of our knowledge, our VSPW is the first attempt to tackle the challenging video scene parsing task in the wild by considering diverse scenarios.

Frame Scene Parsing

Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation

1 code implementation8 Jun 2021 Bingfeng Zhang, Jimin Xiao, Jianbo Jiao, Yunchao Wei, Yao Zhao

More importantly, our approach can be readily applied to bounding box supervised instance segmentation task or other weakly supervised semantic segmentation tasks, with state-of-the-art or comparable performance among almot all weakly supervised tasks on PASCAL VOC or COCO dataset.

Instance Segmentation Weakly-Supervised Semantic Segmentation

Domain Consensus Clustering for Universal Domain Adaptation

1 code implementation CVPR 2021 Guangrui Li, Guoliang Kang, Yi Zhu, Yunchao Wei, Yi Yang

To better exploit the intrinsic structure of the target domain, we propose Domain Consensus Clustering (DCC), which exploits the domain consensus knowledge to discover discriminative clusters on both common samples and private ones.

Open Set Learning Partial Domain Adaptation +1

Associating Objects with Transformers for Video Object Segmentation

2 code implementations NeurIPS 2021 Zongxin Yang, Yunchao Wei, Yi Yang

The state-of-the-art methods learn to decode features with a single positive object and thus have to match and segment each target separately under multi-object scenarios, consuming multiple times computing resources.

One-shot visual object segmentation Semantic Segmentation +1

Cross-Modal Progressive Comprehension for Referring Segmentation

1 code implementation15 May 2021 Si Liu, Tianrui Hui, Shaofei Huang, Yunchao Wei, Bo Li, Guanbin Li

In this paper, we propose a Cross-Modal Progressive Comprehension (CMPC) scheme to effectively mimic human behaviors and implement it as a CMPC-I (Image) module and a CMPC-V (Video) module to improve referring image and video segmentation models.

Referring Expression Segmentation Semantic Segmentation +2

Decoupled Spatial Temporal Graphs for Generic Visual Grounding

no code implementations18 Mar 2021 Qianyu Feng, Yunchao Wei, MingMing Cheng, Yi Yang

Visual grounding is a long-lasting problem in vision-language understanding due to its diversity and complexity.

Contrastive Learning Visual Grounding

AINet: Association Implantation for Superpixel Segmentation

no code implementations ICCV 2021 Yaxiong Wang, Yunchao Wei, Xueming Qian, Li Zhu, Yi Yang

However, simply applying a series of convolution operations with limited receptive fields can only implicitly perceive the relations between the pixel and its surrounding grids.


Towards Complete Scene and Regular Shape for Distortion Rectification by Curve-Aware Extrapolation

no code implementations ICCV 2021 Kang Liao, Chunyu Lin, Yunchao Wei, Feng Li, Shangrong Yang, Yao Zhao

To our knowledge, we are the first to tackle the challenging rectification via outpainting, and our curve-aware strategy can reach a rectification construction with complete content and regular shape.

Consistent Structural Relation Learning for Zero-Shot Segmentation

no code implementations NeurIPS 2020 Peike Li, Yunchao Wei, Yi Yang

Concretely, by exploring the pair-wise and list-wise structures, we impose the relations of generated visual features to be consistent with their counterparts in the semantic word embedding space.

Semantic Segmentation Word Embeddings +1

Delving Deep into Label Smoothing

2 code implementations25 Nov 2020 Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou, Yunchao Wei, Qi Han, Zhen Li, Ming-Ming Cheng

Experiments demonstrate that based on the same classification models, the proposed approach can effectively improve the classification performance on CIFAR-100, ImageNet, and fine-grained datasets.

Classification General Classification

Referring Image Segmentation via Cross-Modal Progressive Comprehension

1 code implementation CVPR 2020 Shaofei Huang, Tianrui Hui, Si Liu, Guanbin Li, Yunchao Wei, Jizhong Han, Luoqi Liu, Bo Li

In addition to the CMPC module, we further leverage a simple yet effective TGFE module to integrate the reasoned multimodal features from different levels with the guidance of textual information.

Referring Expression Segmentation Semantic Segmentation

Inter-Image Communication for Weakly Supervised Localization

1 code implementation ECCV 2020 Xiaolin Zhang, Yunchao Wei, Yi Yang

We learn a feature center for each category and realize the global feature consistency by forcing the object features to approach class-specific centers.

Sketch-Guided Scenery Image Outpainting

no code implementations17 Jun 2020 Yaxiong Wang, Yunchao Wei, Xueming Qian, Li Zhu, Yi Yang

In this work, we take the image outpainting one step forward by allowing users to harvest personal custom outpainting results using sketches as the guidance.

Image Outpainting

Omni-supervised Facial Expression Recognition via Distilled Data

no code implementations18 May 2020 Ping Liu, Yunchao Wei, Zibo Meng, Weihong Deng, Joey Tianyi Zhou, Yi Yang

However, the performance of the current state-of-the-art facial expression recognition (FER) approaches is directly related to the labeled data for training.

Facial Expression Recognition

Referring Image Segmentation by Generative Adversarial Learning

no code implementations IEEE 2020 Shuang Qiu, Yao Zhao, Jianbo Jiao, Yunchao Wei, Shikui Wei

To this end, we propose to train the referring image segmentation model in a generative adversarial fashion, which well addresses the distribution similarity problem.

Referring Expression Referring Expression Segmentation +1

VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification

1 code implementation14 Apr 2020 Zhedong Zheng, Tao Ruan, Yunchao Wei, Yi Yang, Tao Mei

This stage relaxes the full alignment between the training and testing domains, as it is agnostic to the target vehicle domain.

Representation Learning Vehicle Re-Identification

Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation

no code implementations2 Apr 2020 Zhonghao Wang, Yunchao Wei, Rogerior Feris, JinJun Xiong, Wen-mei Hwu, Thomas S. Huang, Humphrey Shi

A key challenge of this task is how to alleviate the data distribution discrepancy between the source and target domains, i. e. reducing domain shift.

Domain Adaptation Semantic Segmentation

Memory Aggregation Networks for Efficient Interactive Video Object Segmentation

no code implementations CVPR 2020 Jiaxu Miao, Yunchao Wei, Yi Yang

Interactive video object segmentation (iVOS) aims at efficiently harvesting high-quality segmentation masks of the target object in a video with user interactions.

Interactive Video Object Segmentation Semantic Segmentation +1

Laplacian Denoising Autoencoder

no code implementations30 Mar 2020 Jianbo Jiao, Linchao Bao, Yunchao Wei, Shengfeng He, Honghui Shi, Rynson Lau, Thomas S. Huang

This can be naturally generalized to span multiple scales with a Laplacian pyramid representation of the input data.

Denoising Self-Supervised Learning

Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

1 code implementation CVPR 2020 Zhonghao Wang, Mo Yu, Yunchao Wei, Rogerio Feris, JinJun Xiong, Wen-mei Hwu, Thomas S. Huang, Humphrey Shi

We consider the problem of unsupervised domain adaptation for semantic segmentation by easing the domain shift between the source domain (synthetic data) and the target domain (real data) in this work.

Semantic Segmentation Unsupervised Domain Adaptation

University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization

3 code implementations27 Feb 2020 Zhedong Zheng, Yunchao Wei, Yi Yang

To our knowledge, University-1652 is the first drone-based geo-localization dataset and enables two new tasks, i. e., drone-view target localization and drone navigation.

Drone navigation Drone-view target localization +1

AlignSeg: Feature-Aligned Segmentation Networks

1 code implementation24 Feb 2020 Zilong Huang, Yunchao Wei, Xinggang Wang, Wenyu Liu, Thomas S. Huang, Humphrey Shi

Aggregating features in terms of different convolutional blocks or contextual embeddings has been proven to be an effective way to strengthen feature representations for semantic segmentation.

Semantic Segmentation

Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach

1 code implementation19 Nov 2019 Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Ming-Jie Sun, Kai-Zhu Huang

Such reliable regions are then directly served as ground-truth labels for the parallel segmentation branch, where a newly designed dense energy loss function is adopted for optimization.

Image Classification Weakly-Supervised Semantic Segmentation

Self-Correction for Human Parsing

2 code implementations22 Oct 2019 Peike Li, Yunqiu Xu, Yunchao Wei, Yi Yang

To tackle the problem of learning with label noises, this work introduces a purification strategy, called Self-Correction for Human Parsing (SCHP), to progressively promote the reliability of the supervised labels as well as the learned models.

Human Parsing Human Part Segmentation +1

SPGNet: Semantic Prediction Guidance for Scene Parsing

no code implementations ICCV 2019 Bowen Cheng, Liang-Chieh Chen, Yunchao Wei, Yukun Zhu, Zilong Huang, JinJun Xiong, Thomas Huang, Wen-mei Hwu, Honghui Shi

The multi-scale context module refers to the operations to aggregate feature responses from a large spatial extent, while the single-stage encoder-decoder structure encodes the high-level semantic information in the encoder path and recovers the boundary information in the decoder path.

Pose Estimation Scene Parsing +1

CCNet: Criss-Cross Attention for Semantic Segmentation

2 code implementations ICCV 2019 Zilong Huang, Xinggang Wang, Yunchao Wei, Lichao Huang, Humphrey Shi, Wenyu Liu, Thomas S. Huang

Compared with the non-local block, the proposed recurrent criss-cross attention module requires 11x less GPU memory usage.

Ranked #6 on Semantic Segmentation on FoodSeg103 (using extra training data)

Human Parsing Instance Segmentation +5

Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification

1 code implementation ICCV 2019 Yang Fu, Yunchao Wei, Guanshuo Wang, Yuqian Zhou, Honghui Shi, Thomas Huang

Upon our SSG, we further introduce a clustering-guided semisupervised approach named SSG ++ to conduct the one-shot domain adaption in an open set setting (i. e. the number of independent identities from the target domain is unknown).

One-Shot Learning Unsupervised Domain Adaptation +1

A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization

no code implementations23 Nov 2018 Bowen Cheng, Yunchao Wei, Jiahui Yu, Shiyu Chang, JinJun Xiong, Wen-mei Hwu, Thomas S. Huang, Humphrey Shi

While training on samples drawn from independent and identical distribution has been a de facto paradigm for optimizing image classification networks, humans learn new concepts in an easy-to-hard manner and on the selected examples progressively.

General Classification Image Classification +5

STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

no code implementations9 Nov 2018 Yang Fu, Xiaoyang Wang, Yunchao Wei, Thomas Huang

Thus, a more robust clip-level feature representation can be generated according to a weighted sum operation guided by the mined 2-D attention score matrix.

Frame Large-Scale Person Re-Identification +1

Self-Erasing Network for Integral Object Attention

no code implementations NeurIPS 2018 Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng

To test the quality of the generated attention maps, we employ the mined object regions as heuristic cues for learning semantic segmentation models.

Semantic Segmentation

TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection

no code implementations ECCV 2018 Yunchao Wei, Zhiqiang Shen, Bowen Cheng, Honghui Shi, JinJun Xiong, Jiashi Feng, Thomas Huang

This work provides a simple approach to discover tight object bounding boxes with only image-level supervision, called Tight box mining with Surrounding Segmentation Context (TS2C).

Multiple Instance Learning Weakly Supervised Object Detection +1

Adversarial Complementary Learning for Weakly Supervised Object Localization

2 code implementations CVPR 2018 Xiaolin Zhang, Yunchao Wei, Jiashi Feng, Yi Yang, Thomas Huang

With such an adversarial learning, the two parallel-classifiers are forced to leverage complementary object regions for classification and can finally generate integral object localization together.

General Classification Weakly-Supervised Object Localization

Horizontal Pyramid Matching for Person Re-identification

1 code implementation14 Apr 2018 Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang

Despite the remarkable recent progress, person re-identification (Re-ID) approaches are still suffering from the failure cases where the discriminative body parts are missing.

Person Re-Identification

Left-Right Comparative Recurrent Model for Stereo Matching

no code implementations CVPR 2018 Zequn Jie, Pengfei Wang, Yonggen Ling, Bo Zhao, Yunchao Wei, Jiashi Feng, Wei Liu

Left-right consistency check is an effective way to enhance the disparity estimation by referring to the information from the opposite view.

Disparity Estimation Stereo Disparity Estimation +2

Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

3 code implementations ECCV 2018 Bowen Cheng, Yunchao Wei, Honghui Shi, Rogerio Feris, JinJun Xiong, Thomas Huang

Recent region-based object detectors are usually built with separate classification and localization branches on top of shared feature extraction networks.

Classification General Classification +1

Transferable Semi-supervised Semantic Segmentation

no code implementations18 Nov 2017 Huaxin Xiao, Yunchao Wei, Yu Liu, Maojun Zhang, Jiashi Feng

The performance of deep learning based semantic segmentation models heavily depends on sufficient data with careful annotations.

Semi-Supervised Semantic Segmentation

Learning to Segment Human by Watching YouTube

no code implementations4 Oct 2017 Xiaodan Liang, Yunchao Wei, Liang Lin, Yunpeng Chen, Xiaohui Shen, Jianchao Yang, Shuicheng Yan

An intuition on human segmentation is that when a human is moving in a video, the video-context (e. g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body.

Human Detection Semantic Segmentation +3

Regional Interactive Image Segmentation Networks

no code implementations ICCV 2017 Jun Hao Liew, Yunchao Wei, Wei Xiong, Sim-Heng Ong, Jiashi Feng

The interactive image segmentation model allows users to iteratively add new inputs for refinement until a satisfactory result is finally obtained.

Interactive Segmentation Semantic Segmentation

Self-explanatory Deep Salient Object Detection

no code implementations18 Aug 2017 Huaxin Xiao, Jiashi Feng, Yunchao Wei, Maojun Zhang

Through visualizing the differences, we can interpret the capability of different deep neural networks based saliency detection models and demonstrate that our proposed model indeed uses more reasonable structure for salient object detection.

RGB Salient Object Detection Saliency Prediction +1

Perceptual Generative Adversarial Networks for Small Object Detection

no code implementations CVPR 2017 Jianan Li, Xiaodan Liang, Yunchao Wei, Tingfa Xu, Jiashi Feng, Shuicheng Yan

In this work, we address the small object detection problem by developing a single architecture that internally lifts representations of small objects to "super-resolved" ones, achieving similar characteristics as large objects and thus more discriminative for detection.

Small Object Detection

Multiple-Human Parsing in the Wild

2 code implementations19 May 2017 Jianshu Li, Jian Zhao, Yunchao Wei, Congyan Lang, Yidong Li, Terence Sim, Shuicheng Yan, Jiashi Feng

To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.

Multi-Human Parsing

IAN: The Individual Aggregation Network for Person Search

no code implementations16 May 2017 Jimin Xiao, Yanchun Xie, Tammam Tillo, Kai-Zhu Huang, Yunchao Wei, Jiashi Feng

In addition, to relieve the negative effect caused by varying visual appearances of the same individual, IAN introduces a novel center loss that can increase the intra-class compactness of feature representations.

Object Detection Person Search

Deep Self-Taught Learning for Weakly Supervised Object Localization

no code implementations CVPR 2017 Zequn Jie, Yunchao Wei, Xiaojie Jin, Jiashi Feng, Wei Liu

To overcome this issue, we propose a deep self-taught learning approach, which makes the detector learn the object-level features reliable for acquiring tight positive samples and afterwards re-train itself based on them.

Weakly Supervised Object Detection Weakly-Supervised Object Localization

Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach

no code implementations CVPR 2017 Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, Shuicheng Yan

We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems.

Classification General Classification +1

Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation

no code implementations7 Dec 2016 Qinbin Hou, Puneet Kumar Dokania, Daniela Massiceti, Yunchao Wei, Ming-Ming Cheng, Philip Torr

We focus on the following three aspects of EM: (i) initialization; (ii) latent posterior estimation (E-step) and (iii) the parameter update (M-step).

Weakly-Supervised Semantic Segmentation

Attentive Contexts for Object Detection

no code implementations24 Mar 2016 Jianan Li, Yunchao Wei, Xiaodan Liang, Jian Dong, Tingfa Xu, Jiashi Feng, Shuicheng Yan

We provide preliminary answers to these questions through developing a novel Attention to Context Convolution Neural Network (AC-CNN) based object detection model.

Object Detection

Instance-Aware Hashing for Multi-Label Image Retrieval

no code implementations10 Mar 2016 Hanjiang Lai, Pan Yan, Xiangbo Shu, Yunchao Wei, Shuicheng Yan

The instance-aware representations not only bring advantages to semantic hashing, but also can be used in category-aware hashing, in which an image is represented by multiple pieces of hash codes and each piece of code corresponds to a category.

Multi-Label Image Retrieval

Deep Learning with S-shaped Rectified Linear Activation Units

1 code implementation22 Dec 2015 Xiaojie Jin, Chunyan Xu, Jiashi Feng, Yunchao Wei, Junjun Xiong, Shuicheng Yan

Rectified linear activation units are important components for state-of-the-art deep convolutional networks.

Reversible Recursive Instance-level Object Segmentation

no code implementations CVPR 2016 Xiaodan Liang, Yunchao Wei, Xiaohui Shen, Zequn Jie, Jiashi Feng, Liang Lin, Shuicheng Yan

By being reversible, the proposal refinement sub-network adaptively determines an optimal number of refinement iterations required for each proposal during both training and testing.

Denoising Semantic Segmentation

STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

1 code implementation10 Sep 2015 Yunchao Wei, Xiaodan Liang, Yunpeng Chen, Xiaohui Shen, Ming-Ming Cheng, Jiashi Feng, Yao Zhao, Shuicheng Yan

Then, a better network called Enhanced-DCNN is learned with supervision from the predicted segmentation masks of simple images based on the Initial-DCNN as well as the image-level annotations.

RGB Salient Object Detection Salient Object Detection +1

Modality-dependent Cross-media Retrieval

no code implementations22 Jun 2015 Yunchao Wei, Yao Zhao, Zhenfeng Zhu, Shikui Wei, Yanhui Xiao, Jiashi Feng, Shuicheng Yan

Specifically, by jointly optimizing the correlation between images and text and the linear regression from one modal space (image or text) to the semantic space, two couples of mappings are learned to project images and text from their original feature spaces into two common latent subspaces (one for I2T and the other for T2I).

Computational Baby Learning

no code implementations11 Nov 2014 Xiaodan Liang, Si Liu, Yunchao Wei, Luoqi Liu, Liang Lin, Shuicheng Yan

Then the concept detector can be fine-tuned based on these new instances.

Object Detection

CNN: Single-label to Multi-label

no code implementations22 Jun 2014 Yunchao Wei, Wei Xia, Junshi Huang, Bingbing Ni, Jian Dong, Yao Zhao, Shuicheng Yan

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks.

Image Classification

Proximal Iteratively Reweighted Algorithm with Multiple Splitting for Nonconvex Sparsity Optimization

no code implementations28 Apr 2014 Canyi Lu, Yunchao Wei, Zhouchen Lin, Shuicheng Yan

This paper proposes the Proximal Iteratively REweighted (PIRE) algorithm for solving a general problem, which involves a large body of nonconvex sparse and structured sparse related problems.

Cannot find the paper you are looking for? You can Submit a new open access paper.