2 citations · 3 across the 3 of their papers we have counts for
8 papers
Iterative Geometry-Aware Cross Guidance Network for Stereo Image Inpainting
Ang Li, Shanshan Zhao, Qingjie Zhang +1
Currently, single image inpainting has achieved promising results based on deep convolutional neural networks. However, inpainting on stereo images with missing regions has not bee…
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma +4
Deep image inpainting aims to restore damaged or missing regions in an image with realistic contents. While having a wide range of applications such as object removal and image rec…
Short-Term and Long-Term Context Aggregation Network for Video Inpainting
Ang Li, Shanshan Zhao, Xingjun Ma +5
Video inpainting aims to restore missing regions of a video and has many applications such as video editing and object removal. However, existing methods either suffer from inaccur…
Boosted GAN with Semantically Interpretable Information for Image Inpainting
Ang Li, Jianzhong Qi, Rui Zhang +1
Image inpainting aims at restoring missing region of corrupted images, which has many applications such as image restoration and object removal. However, current GAN-based inpainti…
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
Xue Yang, Junchi Yan, Ziming Feng +1
Rotation detection is a challenging task due to the difficulties of locating the multi-angle objects and separating them effectively from the background. Though considerable progre…
Generative Image Inpainting with Submanifold Alignment
Ang Li, Jianzhong Qi, Rui Zhang +2
Image inpainting aims at restoring missing regions of corrupted images, which has many applications such as image restoration and object removal. However, current GAN-based generat…