Coarse-to-Fine Visual Question Answering by Iterative, Conditional Refinement

Visual Question Answering (VQA) is a very interesting tech nique to answer natural language questions about an image. Recent methods have focused on incorporating knowledge into an improved VQA model, by augmenting the training set, representing scene graphs, or including reasoning. We also leverage knowledge to make VQA more robust. Yet we take...

A triplet-learnt Coarse-to-Fine Reranking for Large Scale Vehicle Re-identification.

Vehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the...

Fast and accurate person re-identification with xception conv-net and C2F

Person re-identification (re-id) is the task of identifying a person of interest across disjoint camera views in a multi-camera system. This is a challenging problem due to the different poses, viewpoints and lighting conditions. Deeply learned systems have become prevalent in the person re-identification field as they are capable to deal with...