Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …

People with hearing impairments are found worldwide; therefore, the development of
effective local level sign language recognition (SLR) tools is essential. We conducted a …

Temporal modeling of objects is a key challenge in multiple-object tracking (MOT). Existing
methods track by associating detections through motion-based and appearance-based …

Sign languages are visual languages using manual articulations and non-manual elements
to convey information. For sign language recognition and translation, the majority of existing …

This paper proposes a simple transfer learning baseline for sign language translation.
Existing sign language datasets (eg PHOENIX-2014T, CSL-Daily) contain only about 10K …

In this paper we present a system for word-level sign language recognition based on the
Transformer model. We aim at a solution with low computational cost, since we see great …

Transformer models have shown great success handling long-range interactions, making
them a promising tool for modeling video. However, they lack inductive biases and scale …

Sign language recognition (SLR) is a weakly supervised task that annotates sign videos as
textual glosses. Recent studies show that insufficient training caused by the lack of large …

Despite existing pioneering works on sign language translation (SLT), there is a non-trivial
obstacle, ie, the limited quantity of parallel sign-text data. To tackle this parallel data …

One of the factors that have hindered progress in the areas of sign language recognition,
translation, and production is the absence of large annotated datasets. Towards this end, we …