5 citations · 17 across the 9 of their papers we have counts for
10 papers
Rethinking Monocular Depth Embedding for Generalized Stereo Matching
Libo Lin, Shuangli Du, Minghua Zhao +3
Generally, monocular methods capture rich contextual priors but lack geometric precision, whereas stereo methods are geometrically accurate yet struggle in textureless and occluded…
Prototype-Based Pseudo-Label Denoising for Source-Free Domain Adaptation in Remote Sensing Semantic Segmentation
Bin Wang, Fei Deng, Zeyu Chen +2
Source-Free Domain Adaptation (SFDA) enables domain adaptation for semantic segmentation of Remote Sensing Images (RSIs) using only a well-trained source model and unlabeled target…
Low-light Stereo Image Enhancement and De-noising in the Low-frequency Information Enhanced Image Space
Minghua Zhao, Xiangdong Qin, Shuangli Du +3
Unlike single image task, stereo image enhancement can use another view information, and its key stage is how to perform cross-view feature interaction to extract useful informatio…
PHI-MVS: Plane Hypothesis Inference Multi-view Stereo for Large-Scale Scene Reconstruction
Shang Sun, Yunan Zheng, Xuelei Shi +2
PatchMatch based Multi-view Stereo (MVS) algorithms have achieved great success in large-scale scene reconstruction tasks. However, reconstruction of texture-less planes often fail…
Learning Structral coherence Via Generative Adversarial Network for Single Image Super-Resolution
Yuanzhuo Li, Yunan Zheng, Jie Chen +2
Among the major remaining challenges for single image super resolution (SISR) is the capacity to recover coherent images with global shapes and local details conforming to human vi…
Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation
Lihua Zhou, Mao Ye, Xinpeng Li +3
Recent works in domain adaptation always learn domain invariant features to mitigate the gap between the source and target domains by adversarial methods. The category information…
Complex-order Derivative and Integral Filters and its Applications
Yiguang Liu
In this paper, complex-order derivative and integral filters are proposed, which are consistent with the filters with fractional derivative and integral orders. Compared with the f…
A Unifying Decomposition and Reconstruction Model for Discrete Signals
Yiguang Liu
Decomposing discrete signals such as images into components is vital in many applications, and this paper propose a framework to produce filtering banks to accomplish this task. Th…
Study on Sparse Representation based Classification for Biometric Verification
Zengxi Huang, Yiguang Liu, Xiaoming Wang +1
In this paper, we propose a multimodal verification system integrating face and ear based on sparse representation based classification (SRC). The face and ear query samples are fi…
A random algorithm for low-rank decomposition of large-scale matrices with missing entries
Yiguang Liu
A Random SubMatrix method (RSM) is proposed to calculate the low-rank decomposition of large-scale matrices with known entry percentage ρ. RSM is very fast as the floating-point op…