Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

4 code implementations • ECCV 2020 • Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiao-Wei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, Yejin Choi, Jianfeng Gao

Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks.

Image Captioning Image Retrieval +3

Instance Shadow Detection

3 code implementations • CVPR 2020 • Tianyu Wang, Xiao-Wei Hu, Qiong Wang, Pheng-Ann Heng, Chi-Wing Fu

Then, we pair up the predicted shadow and object instances, and match them with the predicted shadow-object associations to generate the final results.

Instance Shadow Detection Object +1

CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading

1 code implementation • 4 Nov 2019 • Xiaomeng Li, Xiao-Wei Hu, Lequan Yu, Lei Zhu, Chi-Wing Fu, Pheng-Ann Heng

In this paper, we present a novel cross-disease attention network (CANet) to jointly grade DR and DME by exploring the internal relationship between the diseases with only image-level supervision.

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

1 code implementation • 3 Jul 2019 • Yi Wang, Haoran Dou, Xiao-Wei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin, Pheng-Ann Heng, Tianfu Wang, Dong Ni

Our attention module utilizes the attention mechanism to selectively leverage the multilevel features integrated from different layers to refine the features at each individual layer, suppressing the non-prostate noise at shallow layers of the CNN and increasing more prostate details into features at deep layers.

Image Segmentation Medical Image Segmentation +2

Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection

1 code implementation • ECCV 2018 • Lei Zhu, Zijun Deng, Xiao-Wei Hu, Chi-Wing Fu, Xuemiao Xu, Jing Qin, Pheng-Ann Heng

Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.

Shadow Detection

Richer Convolutional Features for Edge Detection

3 code implementations • CVPR 2017 • Yun Liu, Ming-Ming Cheng, Xiao-Wei Hu, Kai Wang, Xiang Bai

Using VGG16 network, we achieve \sArt results on several available datasets.

Edge Detection

Deeply supervised salient object detection with short connections

4 code implementations • CVPR 2017 • Qibin Hou, Ming-Ming Cheng, Xiao-Wei Hu, Ali Borji, Zhuowen Tu, Philip Torr

Recent progress on saliency detection is substantial, benefiting mostly from the explosive development of Convolutional Neural Networks (CNNs).

Boundary Detection Object +5