305 citations · 654 across the 23 of their papers we have counts for
23 papers
Limb-Aware Virtual Try-On Network with Progressive Clothing Warping
Shengping Zhang, Xiaoyu Han, Weigang Zhang +3
Image-based virtual try-on aims to transfer an in-shop clothing image to a person image. Most existing methods adopt a single global deformation to perform clothing warping directl…
Progressive Limb-Aware Virtual Try-On
Xiaoyu Han, Shengping Zhang, Qinglin Liu +2
Existing image-based virtual try-on methods directly transfer specific clothing to a human image without utilizing clothing attributes to refine the transferred clothing geometry a…
End-to-End Human Instance Matting
Qinglin Liu, Shengping Zhang, Quanling Meng +3
Human instance matting aims to estimate an alpha matte for each human instance in an image, which is extremely challenging and has rarely been studied so far. Despite some efforts…
CaPhy: Capturing Physical Properties for Animatable Human Avatars
Zhaoqi Su, Liangxiao Hu, Siyou Lin +4
We present CaPhy, a novel method for reconstructing animatable human avatars with realistic dynamic properties for clothing. Specifically, we aim for capturing the geometric and ph…
Revisiting Context Aggregation for Image Matting
Qinglin Liu, Xiaoqian Lv, Quanling Meng +5
Traditional studies emphasize the significance of context information in improving matting performance. Consequently, deep learning-based matting methods delve into designing pooli…
Long-Range Feature Propagating for Natural Image Matting
Qinglin Liu, Haozhe Xie, Shengping Zhang +2
Natural image matting estimates the alpha values of unknown regions in the trimap. Recently, deep learning based methods propagate the alpha values from the known regions to unknow…
Efficient Regional Memory Network for Video Object Segmentation
Haozhe Xie, Hongxun Yao, Shangchen Zhou +2
Recently, several Space-Time Memory based networks have shown that the object cues (e.g. video frames as well as the segmented object masks) from the past frames are useful for seg…
Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy
Zikai Zhang, Bineng Zhong, Shengping Zhang +3
A practical long-term tracker typically contains three key properties, i.e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness m…
Continuous Prediction of Lower-Limb Kinematics From Multi-Modal Biomedical Signals
Chunzhi Yi, Feng Jiang, Shengping Zhang +6
The fast-growing techniques of measuring and fusing multi-modal biomedical signals enable advanced motor intent decoding schemes of lowerlimb exoskeletons, meeting the increasing d…
Object-and-Action Aware Model for Visual Language Navigation
Yuankai Qi, Zizheng Pan, Shengping Zhang +2
Vision-and-Language Navigation (VLN) is unique in that it requires turning relatively general natural-language instructions into robot agent actions, on the basis of the visible en…
GRNet: Gridding Residual Network for Dense Point Cloud Completion
Haozhe Xie, Hongxun Yao, Shangchen Zhou +3
Estimating the complete 3D point cloud from an incomplete one is a key problem in many vision and robotics applications. Mainstream methods (e.g., PCN and TopNet) use Multi-layer P…
Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images
Haozhe Xie, Hongxun Yao, Shengping Zhang +2
Recovering the 3D shape of an object from single or multiple images with deep neural networks has been attracting increasing attention in the past few years. Mainstream works (e.g.…
Scene Text Recognition via Transformer
Xinjie Feng, Hongxun Yao, Yuankai Qi +2
Scene text recognition with arbitrary shape is very challenging due to large variations in text shapes, fonts, colors, backgrounds, etc. Most state-of-the-art algorithms rectify th…
Siamese Box Adaptive Network for Visual Tracking
Zedu Chen, Bineng Zhong, Guorong Li +2
Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target. Unfor…
Toward 3D Object Reconstruction from Stereo Images
Haozhe Xie, Hongxun Yao, Shangchen Zhou +3
Inferring the 3D shape of an object from an RGB image has shown impressive results, however, existing methods rely primarily on recognizing the most similar 3D model from the train…
Sketch-Specific Data Augmentation for Freehand Sketch Recognition
Ying Zheng, Hongxun Yao, Xiaoshuai Sun +3
Sketch recognition remains a significant challenge due to the limited training data and the substantial intra-class variance of freehand sketches for the same object. Conventional…
Light Field Saliency Detection with Deep Convolutional Networks
Jun Zhang, Yamei Liu, Shengping Zhang +2
Light field imaging presents an attractive alternative to RGB imaging because of the recording of the direction of the incoming light. The detection of salient regions in a light f…
DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks
Jun Zhang, Tong Zheng, Shengping Zhang +1
Computational color constancy refers to the estimation of the scene illumination and makes the perceived color relatively stable under varying illumination. In the past few years,…
Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images
Haozhe Xie, Hongxun Yao, Xiaoshuai Sun +2
Recovering the 3D representation of an object from single-view or multi-view RGB images by deep neural networks has attracted increasing attention in the past few years. Several ma…
Convolutional Neural Networks based Intra Prediction for HEVC
Wenxue Cui, Tao Zhang, Shengping Zhang +3
Traditional intra prediction methods for HEVC rely on using the nearest reference lines for predicting a block, which ignore much richer context between the current block and its n…
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratios
Wenxue Cui, Heyao Xu, Xinwei Gao +3
The compressed sensing (CS) has been successfully applied to image compression in the past few years as most image signals are sparse in a certain domain. Several CS reconstruction…
Deep Networks for Compressed Image Sensing
Wuzhen Shi, Feng Jiang, Shengping Zhang +1
The compressed sensing (CS) theory has been successfully applied to image compression in the past few years as most image signals are sparse in a certain domain. Several CS reconst…
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?
Yashar Deldjoo, Shengping Zhang, Bahman Zanj +2
Recently, sparse representation based visual tracking methods have attracted increasing attention in the computer vision community. Although achieve superior performance to traditi…