Search Results for author: Qingzhong Wang

Found 23 papers, 13 papers with code

TiC: Exploring Vision Transformer in Convolution

1 code implementation6 Oct 2023 Song Zhang, Qingzhong Wang, Jiang Bian, Haoyi Xiong

While models derived from Vision Transformers (ViTs) have been phonemically surging, pre-trained models cannot seamlessly adapt to arbitrary resolution images without altering the architecture and configuration, such as sampling the positional encoding, limiting their flexibility for various vision tasks.

Image Classification

CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation

no code implementations6 Oct 2023 Weibin Liao, Xuhong LI, Qingzhong Wang, Yanwu Xu, Zhaozheng Yin, Haoyi Xiong

While pre-training on object detection tasks, such as Common Objects in Contexts (COCO) [1], could significantly boost the performance of cell segmentation, it still consumes on massive fine-annotated cell images [2] with bounding boxes, masks, and cell types for every cell in every image, to fine-tune the pre-trained model.

Cell Segmentation Contrastive Learning +6

MUSCLE: Multi-task Self-supervised Continual Learning to Pre-train Deep Models for X-ray Images of Multiple Body Parts

no code implementations3 Oct 2023 Weibin Liao, Haoyi Xiong, Qingzhong Wang, Yan Mo, Xuhong LI, Yi Liu, Zeyu Chen, Siyu Huang, Dejing Dou

In this work, we study a novel self-supervised pre-training pipeline, namely Multi-task Self-super-vised Continual Learning (MUSCLE), for multiple medical imaging tasks, such as classification and segmentation, using X-ray images collected from multiple body parts, including heads, lungs, and bones.

Continual Learning Representation Learning +1

Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks

no code implementations24 Feb 2023 Yuxuan Zhang, Qingzhong Wang, Jiang Bian, Yi Liu, Yanwu Xu, Dejing Dou, Haoyi Xiong

Due to the high similarity between MRI data and videos, we conduct extensive empirical studies on video recognition techniques for MRI classification to answer the questions: (1) can we directly use video recognition models for MRI classification, (2) which model is more appropriate for MRI, (3) are the common tricks like data augmentation in video recognition still useful for MRI classification?

Classification Data Augmentation +3

Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN

1 code implementation5 Aug 2022 Yongsong Huang, Qingzhong Wang, Shinichiro Omachi

To the best of our knowledge, this is the first composite degradation model proposed for radiographic images.

Denoising Generative Adversarial Network +1

P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos

no code implementations26 Jul 2022 Jiang Bian, Xuhong LI, Tao Wang, Qingzhong Wang, Jun Huang, Chen Liu, Jun Zhao, Feixiang Lu, Dejing Dou, Haoyi Xiong

While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging.

Action Detection Action Localization +2

Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios

no code implementations4 Jul 2022 Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li, Haoyi Xiong, Dejing Dou, Antoni B. Chan

In this paper, we propose a sampling scheme, Monte-Carlo Pareto Optimization for Active Learning (POAL), which selects optimal subsets of unlabeled samples with fixed batch size from the unlabeled data pool.

Active Learning

A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications

1 code implementation2 Jun 2022 Fei Wu, Qingzhong Wang, Jian Bian, Haoyi Xiong, Ning Ding, Feixiang Lu, Jun Cheng, Dejing Dou

Finally, we discuss the challenges and unsolved problems in this area and to facilitate sports analytics, we develop a toolbox using PaddlePaddle, which supports football, basketball, table tennis and figure skating action recognition.

Action Recognition Sports Analytics +1

A Simple yet Effective Framework for Active Learning to Rank

no code implementations20 May 2022 Qingzhong Wang, Haifang Li, Haoyi Xiong, Wen Wang, Jiang Bian, Yu Lu, Shuaiqiang Wang, Zhicong Cheng, Dejing Dou, Dawei Yin

To handle the diverse query requests from users at web-scale, Baidu has done tremendous efforts in understanding users' queries, retrieve relevant contents from a pool of trillions of webpages, and rank the most relevant webpages on the top of results.

Active Learning Learning-To-Rank

On Distinctive Image Captioning via Comparing and Reweighting

no code implementations8 Apr 2022 Jiuniu Wang, Wenjia Xu, Qingzhong Wang, Antoni B. Chan

First, we propose a distinctiveness metric -- between-set CIDEr (CIDErBtw) to evaluate the distinctiveness of a caption with respect to those of similar images.

Image Captioning Retrieval +1

A Comparative Survey of Deep Active Learning

1 code implementation25 Mar 2022 Xueying Zhan, Qingzhong Wang, Kuan-Hao Huang, Haoyi Xiong, Dejing Dou, Antoni B. Chan

In this work, We construct a DAL toolkit, DeepAL+, by re-implementing 19 highly-cited DAL methods.

Active Learning

AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators

1 code implementation21 Sep 2021 Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang

Most of the existing contrastive learning methods employ pre-defined view generation methods, e. g., node drop or edge perturbation, which usually cannot adapt to input data or preserve the original semantic structures well.

Contrastive Learning Graph Representation Learning +3

Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN

no code implementations2 Sep 2021 Yongsong Huang, Zetao Jiang, Qingzhong Wang, Qi Jiang, Guoming Pang

Recently, deep learning methods have dominated image super-resolution and achieved remarkable performance on visible images; however, IR images have received less attention.

Image Super-Resolution Infrared image super-resolution

Group-based Distinctive Image Captioning with Memory Attention

no code implementations20 Aug 2021 Jiuniu Wang, Wenjia Xu, Qingzhong Wang, Antoni B. Chan

In particular, we propose a group-based memory attention (GMA) module, which stores object features that are unique among the image group (i. e., with low similarity to objects in other images).

Contrastive Learning Image Captioning +1

Face.evoLVe: A High-Performance Face Recognition Library

1 code implementation19 Jul 2021 Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao

In this paper, we develop face. evoLVe -- a comprehensive library that collects and implements a wide range of popular deep learning-based methods for face recognition.

Face Alignment Face Recognition +1

Generating Person Images with Appearance-aware Pose Stylizer

1 code implementation17 Jul 2020 Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng, Qingzhong Wang, Xingran Zhou, Bihan Wen, Jun Huan, Dejing Dou

Generation of high-quality person images is challenging, due to the sophisticated entanglements among image factors, e. g., appearance, pose, foreground, background, local details, global structures, etc.

Image Generation

Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets

no code implementations ECCV 2020 Jiuniu Wang, Wenjia Xu, Qingzhong Wang, Antoni B. Chan

A wide range of image captioning models has been developed, achieving significant improvement based on popular metrics, such as BLEU, CIDEr, and SPICE.

Image Captioning Retrieval

Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions

1 code implementation14 May 2020 Di Hu, Lichao Mou, Qingzhong Wang, Junyu. Gao, Yuansheng Hua, Dejing Dou, Xiao Xiang Zhu

Visual crowd counting has been recently studied as a way to enable people counting in crowd scenes from images.

Crowd Counting

Parameter-Free Style Projection for Arbitrary Style Transfer

1 code implementation17 Mar 2020 Siyu Huang, Haoyi Xiong, Tianyang Wang, Bihan Wen, Qingzhong Wang, Zeyu Chen, Jun Huan, Dejing Dou

This paper further presents a real-time feed-forward model to leverage Style Projection for arbitrary image style transfer, which includes a regularization term for matching the semantics between input contents and stylized outputs.

Style Transfer

Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point Process

1 code implementation14 Aug 2019 Qingzhong Wang, Antoni B. Chan

Although significant progress has been made in the field of automatic image captioning, it is still a challenging task.

Image Captioning Reinforcement Learning (RL)

Describing like humans: on diversity in image captioning

1 code implementation CVPR 2019 Qingzhong Wang, Antoni B. Chan

We find that there is still a large gap between the model and human performance in terms of both accuracy and diversity and the models that have optimized accuracy (CIDEr) have low diversity.

Image Captioning

Gated Hierarchical Attention for Image Captioning

1 code implementation30 Oct 2018 Qingzhong Wang, Antoni B. Chan

Attention modules connecting encoder and decoders have been widely applied in the field of object recognition, image captioning, visual question answering and neural machine translation, and significantly improves the performance.

Decoder Image Captioning +3

CNN+CNN: Convolutional Decoders for Image Captioning

1 code implementation23 May 2018 Qingzhong Wang, Antoni B. Chan

We also test our model on the paragraph annotation dataset, and get higher CIDEr score compared with hierarchical LSTMs

Image Captioning Sentence

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