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Learning to Detect a Salient Object
  • Tie Liu, Zejian Yuan, +4 authors H. Shum
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 February 2011
In this paper, we study the salient object detection problem for images. We formulate this problem as a binary labeling task where we separate the salient object from the background. We propose a setExpand
Stereo Matching Using Belief Propagation
TLDR
In this paper, we formulate the stereo matching problem as a Markov network consisting of three coupled Markov random fields (MRF's). Expand
Plenoptic sampling
TLDR
We study the problem of plenoptic sampling in image-based rendering (IBR). Expand
Image completion with structure propagation
TLDR
In this paper, we introduce a novel approach to image completion, which we call structure propagation. Expand
Real-time texture synthesis by patch-based sampling
TLDR
We present an algorithm for synthesizing textures from an input sample by sampling patches according to a nonparametric estimation of the local conditional MRF density function, we avoid mismatching features across patch boundaries. Expand
Rendering with concentric mosaics
TLDR
An image based system and process for rendering novel views of a real or synthesized 3D scene based on a series of concentric mosaics depicting the scene. Expand
Lazy snapping
TLDR
In this paper, we present Lazy Snapping, an interactive image cutout tool. Expand
Image super-resolution using gradient profile prior
TLDR
We propose an image super-resolution approach using a novel gradient profile prior, which is a parametric prior describing the shape and the sharpness of the image gradients. Expand
Full-frame video stabilization with motion inpainting
TLDR
Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. Expand
Face Hallucination: Theory and Practice
TLDR
In this paper, we study face hallucination, or synthesizing a high-resolution face image from an input low-resolution image, with the help of a large collection of other high- resolution face images. Expand
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