Argumentation mining aims at automatically extracting structured arguments from
unstructured textual documents. It has recently become a hot topic also due to its potential in …

Taking time to identify expected products and waiting for the checkout in a retail store are
common scenes we all encounter in our daily lives. The realization of automatic product …

Deep learning with noisy labels is practically challenging, as the capacity of deep models is
so high that they can totally memorize these noisy labels sooner or later during training …

Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …

State-of-the-art methods for zero-shot visual recognition formulate learning as a joint
embedding problem of images and side information. In these formulations the current best …

We present a novel latent embedding model for learning a compatibility function between
image and class embeddings, in the context of zero-shot classification. The proposed …

In this paper we introduce a new game to crowd-source natural language referring
expressions. By designing a two player game, we can both collect and verify referring …

Image classification has advanced significantly in recent years with the availability of large-
scale image sets. However, fine-grained classification remains a major challenge due to the …

While 3D object representations are being revived in the context of multi-view object class
detection and scene understanding, they have not yet attained wide-spread use in fine …

Semantic part localization can facilitate fine-grained categorization by explicitly isolating
subtle appearance differences associated with specific object parts. Methods for pose …