8 accepted papers
Existing image enhancement methods fall short of expectations because with them it is difficult to improve global and local image contrast simultaneously. To address this problem, we propose a histogram equalization-based method that adapts to the data-dependent requirements of brightness enhancemen…
We propose a trilingual semantic embedding model that associates visual objects in images with segments of speech signals corresponding to spoken words in an unsupervised manner. Unlike the existing models, our model incorporates three different languages, namely, English, Hindi, and Japanese. To bu…
Finding a region of an image which matches to a query from a large number of candidates is a fundamental problem in image processing. The exhaustive nature of the sliding window approach has encouraged works that can reduce the run time by skipping unnecessary windows or pixels that do not play a su…
Sounds provide us with vast amounts of information about surrounding objects and can even remind us visual images of them. Is it possible to implement this noteworthy human ability on machines? In this paper, we study a new task that consists of predicting image recognition results in the form of se…
Subspace clustering is the problem of partitioning data drawn from a union of multiple subspaces. The most popular subspace clustering framework in recent years is the graph clustering-based approach, which performs subspace clustering in two steps: graph construction and graph clustering. Although…
Irregular scene text such as curved, rotated or perspective texts commonly appear in natural scene images due to different camera view points, special design purposes etc. In this work, we propose a text salience map guided model to recognize these arbitrary direction scene texts. We train a deep Fu…
Edited film alignment is the post-production process of finding small parts of unedited footage that temporally and spatially match an edited film. The huge amount of data to be processed makes significant downsampling of the videos essential in real-life applications. Simultaneously, professional u…
The recognition of text in natural scene images is a practical yet challenging task due to the large variations in backgrounds, textures, fonts, and illumination conditions. In this paper, we propose a highly accurate character recognition model by utilizing the representational power of a specially…