Collaborative Summarization of Topic-Related Videos

Large collections of videos are grouped into clusters by a topic keyword, such as Eiffel Tower or Surfing, with many important visual concepts repeating across them. Such a topically close set of videos have mutual influence on each other, which could be used to summarize one of them by exploiting information from others in the set. We build on this intuition to develop a novel approach to extract a summary that simultaneously captures both important particularities arising in the given video, as well as, generalities identified from the set of videos. The topic-related videos provide visual context to identify the important parts of the video being summarized. We achieve this by developing a collaborative sparse optimization method which can be efficiently solved by a half-quadratic minimization algorithm. Our work builds upon the idea of collaborative techniques from information retrieval and natural language processing, which typically use the attributes of other similar objects to predict the attribute of a given object. Experiments on two challenging and diverse datasets well demonstrate the efficacy of our approach over state-of-the-art methods.Comment: CVPR 201

Re-visiting the porter hypothesis.

We provide a new formulation of the Porter hypothesis that we feel is in the spirit of the hypothesis. Under this formulation we find that the Porter hypothesis need not hold universally, and identify conditions under which it may or may not hold. We first consider the case where the abatement costs associated with a technology is exogenously given. In that case stricter government regulation increases the incentive for adopting the new technology if the old and the new technologies are relatively environmentally friendly to begin with. We then consider the case where the abatement costs associated with a technology is endogenously given. We show that the Porter hypothesis is likely to hold if the new technology is significantly more ecient in production compared to the old technology, or if both the technologies are relatively ecient in production. Whereas if both the technologies are relatively inecient, then the Porter hypothesis is unlikely to go through. Thus, under the appropriate conditions, the Porter hypothesis may hold even in a static framework.Porter hypothesis ; Environmental policy ; Research and development

Multi-View Frame Reconstruction with Conditional GAN

Multi-view frame reconstruction is an important problem particularly when multiple frames are missing and past and future frames within the camera are far apart from the missing ones. Realistic coherent frames can still be reconstructed using corresponding frames from other overlapping cameras. We propose an adversarial approach to learn the spatio-temporal representation of the missing frame using conditional Generative Adversarial Network (cGAN). The conditional input to each cGAN is the preceding or following frames within the camera or the corresponding frames in other overlapping cameras, all of which are merged together using a weighted average. Representations learned from frames within the camera are given more weight compared to the ones learned from other cameras when they are close to the missing frames and vice versa. Experiments on two challenging datasets demonstrate that our framework produces comparable results with the state-of-the-art reconstruction method in a single camera and achieves promising performance in multi-camera scenario.Comment: 5 pages, 4 figures, 3 tables, Accepted at IEEE Global Conference on Signal and Information Processing, 201