Search Results for author: JianFeng Wang

Found 24 papers, 11 papers with code

Edge Prior Augmented Networks for Motion Deblurring on Naturally Blurry Images

no code implementations18 Sep 2021 Yuedong Chen, Junjia Huang, JianFeng Wang, Xiaohua Xie

Motion deblurring has witnessed rapid development in recent years, and most of the recent methods address it by using deep learning techniques, with the help of different kinds of prior knowledge.


An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA

no code implementations10 Sep 2021 Zhengyuan Yang, Zhe Gan, JianFeng Wang, Xiaowei Hu, Yumao Lu, Zicheng Liu, Lijuan Wang

To address this challenge, we propose PICa, a simple yet effective method that Prompts GPT3 via the use of Image Captions, for knowledge-based VQA.

Image Captioning Question Answering +1

RSG: A Simple but Effective Module for Learning Imbalanced Datasets

1 code implementation CVPR 2021 JianFeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, Zhenghua Xu

Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes.

Long-tail Learning

End-to-End Semi-Supervised Object Detection with Soft Teacher

2 code implementations16 Jun 2021 Mengde Xu, Zheng Zhang, Han Hu, JianFeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai, Zicheng Liu

This paper presents an end-to-end semi-supervised object detection approach, in contrast to previous more complex multi-stage methods.

 Ranked #1 on Object Detection on COCO minival (using extra training data)

Instance Segmentation Object Detection +2

Convolutional Neural Networks with Gated Recurrent Connections

1 code implementation5 Jun 2021 JianFeng Wang, Xiaolin Hu

The critical element of RCNN is the recurrent convolutional layer (RCL), which incorporates recurrent connections between neurons in the standard convolutional layer.

Object Detection Object Recognition +2

Compressing Visual-linguistic Model via Knowledge Distillation

no code implementations5 Apr 2021 Zhiyuan Fang, JianFeng Wang, Xiaowei Hu, Lijuan Wang, Yezhou Yang, Zicheng Liu

In this paper, we study knowledge distillation (KD) to effectively compress a transformer-based large VL model into a small VL model.

Image Captioning Knowledge Distillation +2

DAP: Detection-Aware Pre-training with Weak Supervision

1 code implementation CVPR 2021 Yuanyi Zhong, JianFeng Wang, Lijuan Wang, Jian Peng, Yu-Xiong Wang, Lei Zhang

This paper presents a detection-aware pre-training (DAP) approach, which leverages only weakly-labeled classification-style datasets (e. g., ImageNet) for pre-training, but is specifically tailored to benefit object detection tasks.

Classification General Classification +3

Adversarial Feature Augmentation and Normalization for Visual Recognition

1 code implementation22 Mar 2021 Tianlong Chen, Yu Cheng, Zhe Gan, JianFeng Wang, Lijuan Wang, Zhangyang Wang, Jingjing Liu

Recent advances in computer vision take advantage of adversarial data augmentation to ameliorate the generalization ability of classification models.

Classification Data Augmentation +1

Anti-adjacency eigenvalues of mixed extension of star graph

no code implementations18 Feb 2021 JianFeng Wang, Xingyu Lei, Mei Lu

This matrix can be interpreted as the opposite of the adjacency matrix, which is instead constructed from the distance matrix of a graph by keeping each row and each column only the distances equal to 1.

Combinatorics 05C50

LLA: Loss-aware Label Assignment for Dense Pedestrian Detection

1 code implementation12 Jan 2021 Zheng Ge, JianFeng Wang, Xin Huang, Songtao Liu, Osamu Yoshie

A joint loss is then defined as the weighted summation of cls and reg losses as the assigning indicator.

Object Detection Pedestrian Detection

Orthogonal Subspace Decomposition: A New Perspective of Learning Discriminative Features for Face Clustering

no code implementations1 Jan 2021 JianFeng Wang, Thomas Lukasiewicz, Zhongchao shi

Learning discriminative node features is the key to further improve the performance of graph-based face clustering.

Face Clustering

The Hoffman program of graphs: old and new

no code implementations24 Dec 2020 JianFeng Wang, Jing Wang, Maurizio Brunetti

The Hoffman program with respect to any real or complex square matrix $M$ associated to a graph $G$ stems from A. J. Hoffman's pioneering work on the limit points for the spectral radius of adjacency matrices of graphs less than $\sqrt{2+\sqrt{5}}$.

Combinatorics 05C50

MiniVLM: A Smaller and Faster Vision-Language Model

no code implementations13 Dec 2020 JianFeng Wang, Xiaowei Hu, Pengchuan Zhang, Xiujun Li, Lijuan Wang, Lei Zhang, Jianfeng Gao, Zicheng Liu

We design a Two-stage Efficient feature Extractor (TEE), inspired by the one-stage EfficientDet network, to significantly reduce the time cost of visual feature extraction by $95\%$, compared to a baseline model.

Language Modelling

TAP: Text-Aware Pre-training for Text-VQA and Text-Caption

no code implementations CVPR 2021 Zhengyuan Yang, Yijuan Lu, JianFeng Wang, Xi Yin, Dinei Florencio, Lijuan Wang, Cha Zhang, Lei Zhang, Jiebo Luo

Due to this aligned representation learning, even pre-trained on the same downstream task dataset, TAP already boosts the absolute accuracy on the TextVQA dataset by +5. 4%, compared with a non-TAP baseline.

Language Modelling Optical Character Recognition +4

End-to-End Object Detection with Fully Convolutional Network

1 code implementation CVPR 2021 JianFeng Wang, Lin Song, Zeming Li, Hongbin Sun, Jian Sun, Nanning Zheng

Mainstream object detectors based on the fully convolutional network has achieved impressive performance.

Object Detection

Hashing-based Non-Maximum Suppression for Crowded Object Detection

1 code implementation22 May 2020 Jianfeng Wang, Xi Yin, Lijuan Wang, Lei Zhang

Considering the intersection-over-union (IoU) as the metric, we propose a simple yet effective hashing algorithm, named IoUHash, which guarantees that the boxes within the same cell are close enough by a lower IoU bound.

Object Detection Region Proposal

Learning to Count Objects with Few Exemplar Annotations

no code implementations20 May 2019 Jianfeng Wang, Rong Xiao, Yandong Guo, Lei Zhang

In this paper, we study the problem of object counting with incomplete annotations.

Object Counting Object Detection

SFace: An Efficient Network for Face Detection in Large Scale Variations

no code implementations18 Apr 2018 Jianfeng Wang, Ye Yuan, Boxun Li, Gang Yu, Sun Jian

A new dataset called 4K-Face is also introduced to evaluate the performance of face detection with extreme large scale variations.

Face Detection Face Recognition

Gated Recurrent Convolution Neural Network for OCR

1 code implementation NeurIPS 2017 Jianfeng Wang, Xiaolin Hu

Its critical component, Gated Recurrent Convolution Layer (GRCL), is constructed by adding a gate to the Recurrent Convolution Layer (RCL), the critical component of RCNN.

General Classification Image Classification +1

Face Attention Network: An Effective Face Detector for the Occluded Faces

1 code implementation20 Nov 2017 Jianfeng Wang, Ye Yuan, Gang Yu

The performance of face detection has been largely improved with the development of convolutional neural network.

Data Augmentation Occluded Face Detection

Group $K$-Means

no code implementations5 Jan 2015 Jianfeng Wang, Shuicheng Yan, Yi Yang, Mohan S. Kankanhalli, Shipeng Li, Jingdong Wang

We study how to learn multiple dictionaries from a dataset, and approximate any data point by the sum of the codewords each chosen from the corresponding dictionary.

Optimized Cartesian $K$-Means

no code implementations16 May 2014 Jianfeng Wang, Jingdong Wang, Jingkuan Song, Xin-Shun Xu, Heng Tao Shen, Shipeng Li

In OCKM, multiple sub codewords are used to encode the subvector of a data point in a subspace.


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