Weakly Supervised Summarization of Web Videos (Supplementary Material)

Semi Supervised Learning in Wild Faces and Videos

We propose an approach for improving unconstrained face recognition based on leveraging weakly labeled web videos. It is easy to obtain videos that are likely to contain a face of interest from sites such as YouTube through issuing queries with a person’s name; however, many examples of faces not belonging to the person of interest will be present. We propose a new technique capable of learning...

FusionSeg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos Supplementary material

Table 1 shows the per video results for the 50 videos from the DAVIS dataset (referred in Table 1 of the main paper). We compare with several semi-supervised and fully automatic baselines. Our method outperforms the per-video best fully automatic and best semi-supervised baseline in 25 out of 50 videos. Table 2 shows the per video results for the 14 videos from the Segtrack-v2 dataset (referred...

Supplementary Material WarpNet: Weakly Supervised Matching for Single-view Reconstruction

Visual Concept Learning from Weakly Labeled Web Videos

Concept detection is a core component of video database search, concerned with the automatic recognition of visually diverse categories of objects (“airplane”), locations (“desert”), or activities (“interview”). The task poses a difficult challenge as the amount of accurately labeled data available for supervised training is limited and coverage of concept classes is poor. In order to overcome ...

Supplementary material: Backtracking ScSPM Image Classifier for Weakly Supervised Top-down Saliency