Abstract. Most current approaches to recognition aim to be scaleinvariant. However, the cues available for recognizing a 300 pixel tall object are qualitatively different from tho...
Abstract. Image segmentation techniques typically require proper weighting of competing data fidelity and regularization terms. Conventionally, the associated parameters are set t...
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
Abstract. In this paper we develop an algorithm for structured prediction that optimizes against complex performance measures, those which are a function of false positive and fals...
We introduce an algorithm to estimate the optimal exposure parameters from the analysis of a single, possibly under- or over-exposed, image. This algorithm relies on a new quantita...
Abstract. Many computer vision problems such as object segmentation or reconstruction can be formulated in terms of labeling a set of pixels or voxels. In certain scenarios, we may...
A technique for calibrating a network of perspective cameras based on their graph of trifocal tensors is presented. After estimating a set of reliable epipolar geometries, a parame...
We present a method for spotting words in the wild, i.e., in real images taken in unconstrained environments. Text found in the wild has a surprising range of difficulty. At one en...
Abstract. We address the problem of detecting human figures in images, taking into account that the image of the human figure may be taken from a range of viewpoints. We capture ...
Abstract. We present a novel single image deblurring method to estimate spatially non-uniform blur that results from camera shake. We use existing spatially invariant deconvolution...