Peng Wang

Multi-Label Image Recognition with Graph Convolutional Networks

The task of multi-label image recognition is to predict a set of object ...
04/07/2019 ∙ by Zhao-Min Chen, et al. ∙ 32 ∙ share

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CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion

Depth Completion deals with the problem of converting a sparse depth map...
11/13/2019 ∙ by Xinjing Cheng, et al. ∙ 32 ∙ share

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A Robust Attentional Framework for License Plate Recognition in the Wild

Recognizing car license plates in natural scene images is an important y...
06/06/2020 ∙ by Linjiang Zhang, et al. ∙ 18 ∙ share

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Real-time Segmentation and Facial Skin Tones Grading

Modern approaches for semantic segmention usually pay too much attention...
12/30/2019 ∙ by Ling Luo, et al. ∙ 17 ∙ share

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Discriminative and Robust Online Learning for Siamese Visual Tracking

The problem of visual object tracking has traditionally been handled by ...
09/06/2019 ∙ by Jinghao Zhou, et al. ∙ 16 ∙ share

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Challenge Closed-book Science Exam: A Meta-learning Based Question Answering System

Prior work in standardized science exams requires support from large tex...
04/26/2020 ∙ by Xinyue Zheng, et al. ∙ 12 ∙ share

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Structured Multimodal Attentions for TextVQA

Text based Visual Question Answering (TextVQA) is a recently raised chal...
06/01/2020 ∙ by Chenyu Gao, et al. ∙ 12 ∙ share

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Learning Depth with Convolutional Spatial Propagation Network

Depth prediction is one of the fundamental problems in computer vision. ...
10/04/2018 ∙ by Xinjing Cheng, et al. ∙ 10 ∙ share

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Neighbourhood Watch: Referring Expression Comprehension via Language-guided Graph Attention Networks

The task in referring expression comprehension is to localise the object...
12/12/2018 ∙ by Peng Wang, et al. ∙ 8 ∙ share

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Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge

Conventional referring expression comprehension (REF) assumes people to ...
06/02/2020 ∙ by Peng Wang, et al. ∙ 8 ∙ share

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Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs

Humans are able to describe image contents with coarse to fine details a...
03/01/2020 ∙ by Shizhe Chen, et al. ∙ 7 ∙ share

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ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

Autonomous driving has attracted remarkable attention from both industry...
11/29/2018 ∙ by Xibin Song, et al. ∙ 6 ∙ share

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Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution

Spectral super-resolution (SSR) aims at generating a hyperspectral image...
03/24/2019 ∙ by Lei Zhang, et al. ∙ 6 ∙ share

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Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation

The problem of cross-modality person re-identification has been receivin...
10/25/2019 ∙ by Shizhou Zhang, et al. ∙ 5 ∙ share

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Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Deep neural networks have achieved remarkable success in single image su...
06/05/2018 ∙ by Lei Zhang, et al. ∙ 4 ∙ share

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Visual Question Answering as Reading Comprehension

Visual question answering (VQA) demands simultaneous comprehension of bo...
11/29/2018 ∙ by Hui Li, et al. ∙ 4 ∙ share

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Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

Depth estimation from a single image is a fundamental problem in compute...
08/01/2018 ∙ by Xinjing Cheng, et al. ∙ 2 ∙ share

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A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching

Seeking consistent point-to-point correspondences between 3D rigid data ...
07/05/2019 ∙ by Jiaqi Yang, et al. ∙ 2 ∙ share

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V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices

One of the primary challenges faced by deep learning is the degree to wh...
07/29/2019 ∙ by Damien Teney, et al. ∙ 2 ∙ share

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Anisotropic Convolutional Networks for 3D Semantic Scene Completion

As a voxel-wise labeling task, semantic scene completion (SSC) tries to ...
04/05/2020 ∙ by Jie Li, et al. ∙ 2 ∙ share

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Towards End-to-End Text Spotting in Natural Scenes

Text spotting in natural scene images is of great importance for many im...
06/14/2019 ∙ by Hui Li, et al. ∙ 1 ∙ share

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Person Re-identification in Aerial Imagery

Nowadays, with the rapid development of consumer Unmanned Aerial Vehicle...
08/14/2019 ∙ by Shizhou Zhang, et al. ∙ 1 ∙ share

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Unsupervised Learning of Geometry with Edge-aware Depth-Normal Consistency

Learning to reconstruct depths in a single image by watching unlabeled v...
11/10/2017 ∙ by Zhenheng Yang, et al. ∙ 0 ∙ share

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Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

In this work, we tackle the problem of car license plate detection and r...
09/26/2017 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Joint Multi-Person Pose Estimation and Semantic Part Segmentation

Human pose estimation and semantic part segmentation are two complementa...
08/10/2017 ∙ by Fangting Xia, et al. ∙ 0 ∙ share

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Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

In this work, we jointly address the problem of text detection and recog...
07/13/2017 ∙ by Hui Li, et al. ∙ 0 ∙ share

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Semantic Instance Segmentation via Deep Metric Learning

We propose a new method for semantic instance segmentation, by first com...
03/30/2017 ∙ by Alireza Fathi, et al. ∙ 0 ∙ share

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A Fast and Compact Saliency Score Regression Network Based on Fully Convolutional Network

Visual saliency detection aims at identifying the most visually distinct...
02/02/2017 ∙ by Xuanyang Xi, et al. ∙ 0 ∙ share

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The VQA-Machine: Learning How to Use Existing Vision Algorithms to Answer New Questions

One of the most intriguing features of the Visual Question Answering (VQ...
12/16/2016 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Exploiting Temporal Information for DCNN-based Fine-Grained Object Classification

Fine-grained classification is a relatively new field that has concentra...
08/01/2016 ∙ by ZongYuan Ge, et al. ∙ 0 ∙ share

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Where to Focus: Query Adaptive Matching for Instance Retrieval Using Convolutional Feature Maps

Instance retrieval requires one to search for images that contain a part...
06/22/2016 ∙ by Jiewei Cao, et al. ∙ 0 ∙ share

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FVQA: Fact-based Visual Question Answering

Visual Question Answering (VQA) has attracted a lot of attention in both...
06/17/2016 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Pushing the Limits of Deep CNNs for Pedestrian Detection

Compared to other applications in computer vision, convolutional neural ...
03/15/2016 ∙ by Qichang Hu, et al. ∙ 0 ∙ share

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Image Captioning and Visual Question Answering Based on Attributes and External Knowledge

Much recent progress in Vision-to-Language problems has been achieved th...
03/09/2016 ∙ by Qi Wu, et al. ∙ 0 ∙ share

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Hi Detector, What's Wrong with that Object? Identifying Irregular Object From Images by Modelling the Detection Score Distribution

In this work, we study the challenging problem of identifying the irregu...
02/14/2016 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Order-aware Convolutional Pooling for Video Based Action Recognition

Most video based action recognition approaches create the video-level re...
01/31/2016 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Compositional Model based Fisher Vector Coding for Image Classification

Deriving from the gradient vector of a generative model of local feature...
01/16/2016 ∙ by Lingqiao Liu, et al. ∙ 0 ∙ share

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Implementation of Training Convolutional Neural Networks

Deep learning refers to the shining branch of machine learning that is b...
06/03/2015 ∙ by Tianyi Liu, et al. ∙ 0 ∙ share

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Joint Object and Part Segmentation using Deep Learned Potentials

Segmenting semantic objects from images and parsing them into their resp...
05/01/2015 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Efficient SDP Inference for Fully-connected CRFs Based on Low-rank Decomposition

Conditional Random Fields (CRF) have been widely used in a variety of co...
04/07/2015 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Temporal Pyramid Pooling Based Convolutional Neural Networks for Action Recognition

Encouraged by the success of Convolutional Neural Networks (CNNs) in ima...
03/04/2015 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications

In computer vision, many problems such as image segmentation, pixel labe...
11/27/2014 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference

We propose a Branch-and-Cut (B&C) method for solving general MAP-MRF inf...
04/20/2014 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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A Fast Semidefinite Approach to Solving Binary Quadratic Problems

Many computer vision problems can be formulated as binary quadratic prog...
04/03/2013 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Training Effective Node Classifiers for Cascade Classification

Cascade classifiers are widely used in real-time object detection. Diffe...
01/10/2013 ∙ by Chunhua Shen, et al. ∙ 0 ∙ share

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Asymmetric Totally-corrective Boosting for Real-time Object Detection

Real-time object detection is one of the core problems in computer visio...
09/16/2010 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Optimally Training a Cascade Classifier

Cascade classifiers are widely used in real-time object detection. Diffe...
08/23/2010 ∙ by Chunhua Shen, et al. ∙ 0 ∙ share

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LACBoost and FisherBoost: Optimally Building Cascade Classifiers

Object detection is one of the key tasks in computer vision. The cascade...
05/22/2010 ∙ by Chunhua Shen, et al. ∙ 0 ∙ share

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Self-Taught Convolutional Neural Networks for Short Text Clustering

Short text clustering is a challenging problem due to its sparseness of ...
01/01/2017 ∙ by Jiaming Xu, et al. ∙ 0 ∙ share

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Explicit Knowledge-based Reasoning for Visual Question Answering

We describe a method for visual question answering which is capable of r...
11/09/2015 ∙ by Peng Wang, et al. ∙ 0 ∙ share

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Peng Wang

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