By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either ...
We propose a novel framework for 3D reassembly, the task of assembling a solid object from its broken pieces. The primary challenge in this under-explored problem is to robustly e...
Devi Parikh, Rahul Sukthankar, Tsuhan Chen, Mei Ch...
This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...