Jian Sun

TL;DR: In this article, a trimap for an image that specifies a background region, a foreground region, and an unknown region for the image wherein a boundary exists between the foreground region and the unknown region and wherein another boundary existed between the unknown regions and the background region is solved by solving a set of Poisson equations having boundary conditions for the two boundaries to provide a matte that distinguishes a foreground regions from a background regions in the unknown Region.

TL;DR: By encoding more information of the original image feature, this approach generates a much more discriminative visual word codebook that is also efficient in terms of both computation and space consumption, without losing the original repeatability of the visual features.

TL;DR: This paper illustrates that Fisher Vector, VLAD and BOF can be uniformly derived in two steps: i Encoding – separately map each local descriptor into a code, and ii Pooling – aggregate all codes from one image into a single vector.

TL;DR: In this article, the semantic segmentation of the image is done by determining a semantic category for each pixel in the image at least in part based on the resulting segment features, which are extracted from the convolutional feature maps.

TL;DR: The NTIRE2021 challenge on burst super-resolution as mentioned in this paper was the first attempt to generate a clean RGB image with 4 times higher resolution given a RAW noisy burst as input.