138 citations · 311 across the 12 of their papers we have counts for
14 papers
Referring Image Segmentation Using Text Supervision
Fang Liu, Yuhao Liu, Yuqiu Kong +5
Existing Referring Image Segmentation (RIS) methods typically require expensive pixel-level or box-level annotations for supervision. In this paper, we observe that the referring t…
Lighting up NeRF via Unsupervised Decomposition and Enhancement
Haoyuan Wang, Xiaogang Xu, Ke Xu +1
Neural Radiance Field (NeRF) is a promising approach for synthesizing novel views, given a set of images and the corresponding camera poses of a scene. However, images photographed…
Structure-Informed Shadow Removal Networks
Yuhao Liu, Qing Guo, Lan Fu +5
Existing deep learning-based shadow removal methods still produce images with shadow remnants. These shadow remnants typically exist in homogeneous regions with low-intensity value…
Harmonizer: Learning to Perform White-Box Image and Video Harmonization
Zhanghan Ke, Chunyi Sun, Lei Zhu +2
Recent works on image harmonization solve the problem as a pixel-wise image translation task via large autoencoders. They have unsatisfactory performances and slow inference speeds…
Bi-directional Object-context Prioritization Learning for Saliency Ranking
Xin Tian, Ke Xu, Xin Yang +3
The saliency ranking task is recently proposed to study the visual behavior that humans would typically shift their attention over different objects of a scene based on their degre…
Geometry-aware Two-scale PIFu Representation for Human Reconstruction
Zheng Dong, Ke Xu, Ziheng Duan +3
Although PIFu-based 3D human reconstruction methods are popular, the quality of recovered details is still unsatisfactory. In a sparse (e.g., 3 RGBD sensors) capture setting, the d…
Learning to Detect Instance-level Salient Objects Using Complementary Image Labels
Xin Tian, Ke Xu, Xin Yang +2
Existing salient instance detection (SID) methods typically learn from pixel-level annotated datasets. In this paper, we present the first weakly-supervised approach to the SID pro…
Location-aware Single Image Reflection Removal
Zheng Dong, Ke Xu, Yin Yang +3
This paper proposes a novel location-aware deep-learning-based single image reflection removal method. Our network has a reflection detection module to regress a probabilistic refl…
Weakly-supervised Salient Instance Detection
Xin Tian, Ke Xu, Xin Yang +2
Existing salient instance detection (SID) methods typically learn from pixel-level annotated datasets. In this paper, we present the first weakly-supervised approach to the SID pro…
Night-time Scene Parsing with a Large Real Dataset
Xin Tan, Ke Xu, Ying Cao +3
Although huge progress has been made on scene analysis in recent years, most existing works assume the input images to be in day-time with good lighting conditions. In this work, w…
DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors
Xin Yang, Haiyang Mei, Jiqing Zhang +4
Recently, single-image super-resolution has made great progress owing to the development of deep convolutional neural networks (CNNs). The vast majority of CNN-based models use a p…
Where Is My Mirror?
Xin Yang, Haiyang Mei, Ke Xu +3
Mirrors are everywhere in our daily lives. Existing computer vision systems do not consider mirrors, and hence may get confused by the reflected content inside a mirror, resulting…
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset
Tianyu Wang, Xin Yang, Ke Xu +3
Removing rain streaks from a single image has been drawing considerable attention as rain streaks can severely degrade the image quality and affect the performance of existing outd…
Image Correction via Deep Reciprocating HDR Transformation
Xin Yang, Ke Xu, Yibing Song +3
Image correction aims to adjust an input image into a visually pleasing one. Existing approaches are proposed mainly from the perspective of image pixel manipulation. They are not…