We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feat...
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
Segmenting arbitrary unions of linear subspaces is an important tool for computer vision tasks such as motion and image segmentation, SfM or object recognition. We segment subspac...
We present a bottom up algebraic approach for segmenting multiple 2D motion models directly from the partial derivatives of an image sequence. Our method fits a polynomial called ...
In this work the problem of automatic decomposition of video into elementary semantic units, known in the literature as scenes, is addressed. Two multi-modal automatic scene segme...