Xianming Liu

Learn More
The linear regression model is a very attractive tool to design effective image interpolation schemes. Some regression-based image interpolation algorithms have been proposed in the literature, in which the objective functions are optimized by ordinary least squares (OLS). However, it is shown that interpolation with OLS may have some undesirable properties(More)
While feedforward deep convolutional neural networks (CNNs) have been a great success in computer vision, it is important to note that the human visual cortex generally contains more feedback than feedforward connections. In this paper, we will briefly introduce the background of feedbacks in the human visual cortex, which motivates us to develop a(More)
Recent years have witnessed the growing popularity of hashing for efficient large-scale similarity search. It has been shown that the hashing quality could be boosted by hash function learning (HFL). In this paper, we study HFL in the context of multimodal data for cross-view similarity search. We present a novel multimodal HFL method, called Parametric(More)
Arguably the most common cause of image degradation is compression. This papers presents a novel approach to restoring JPEG-compressed images. The main innovation is in the approach of exploiting residual redundancies of JPEG code streams and sparsity properties of latent images. The restoration is a sparse coding process carried out jointy in the DCT and.(More)
The Cassini Ultraviolet Imaging Spectrometer (UVIS) observed the extinction of photons from two stars by the atmosphere of Titan during the Titan flyby. Six species were identified and measured: methane, acetylene, ethylene, ethane, diacetylene, and hydrogen cyanide. The observations cover altitudes from 450 to 1600 kilometers above the surface. A mesopause(More)
Representation and measurement are two important issues for saliency models. Different with previous works that learnt sparse features from large scale natural statistics, we propose to learn features from short-term statistics of single images. For saliency measurement, we define background firing rate (BFR) for each sparse feature, and then we propose to(More)
Relatively little information is available on quantitative risks of therapy-induced second malignant neoplasm (SMN) in patients with non-Hodgkin lymphoma (NHL). A nested case-control study was conducted in a cohort of 3412 patients treated for NHL between 1990 and 2006, including 118 patients with SMN and 472 controls. Risks of(More)
In many practical scenarios, image encryption has to be conducted prior to image compression. This has led to the problem of how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this paper, we design a highly efficient image encryption-then-compression (ETC)(More)
Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the(More)
Most previous works on video indexing and recommendation were only based on the content of video itself, without considering the affective analysis of viewers, which is an efficient and important way to reflect viewers' attitudes, feelings and evaluations of videos. In this paper, we propose a novel method to index and recommend videos based on affective(More)