7 accepted papers
Viewpoint shifts significantly change how gestures and facial expressions appear and frequently cause occlusions, posing a critical challenge for robust Sign Language Recognition (SLR). To address this challenge, we exploit the spatial flexibility and computational efficiency of skeleton data and pr…
"Sign Language Translation (SLT) aims to translate sign videos into text sentences. While gloss sequences, the written approximation of sign videos, provide informative alignment supervision for visual representation learning in SLT, the associated high cost of gloss annotations hampers the scalabil…
The co-occurrence signals (e.g., hand shape, facial expression, and lip pattern) play a critical role in Continuous Sign Language Recognition (CSLR). Compared to RGB data, skeleton data provide a more efficient and concise option, and lay a good foundation for the co-occurrence exploration in CSLR.…
"Connectionist Temporal Classification (CTC) is a popular objective function in sequence recognition, which provides supervision for unsegmented sequence data through aligning sequence and its corresponding labeling iteratively. The blank class of CTC plays a crucial role in the alignment process an…
In recent years, deep learning moves video-based Continuous Sign Language Recognition (CSLR) significantly forward. Currently, a typical network combination for CSLR includes a visual module, which focuses on spatial and short-temporal information, followed by a contextual module, which focuses on l…
Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize unsegmented signs from image streams. Overfitting is one of the most critical problems in CSLR training, and previous works show that the iterative training scheme can partially solve this problem while also costing more trai…
Point clouds contain rich spatial information, which provides complementary cues for gesture recognition. In this paper, we formulate gesture recognition as an irregular sequence recognition problem and aim to capture long-term spatial correlations across point cloud sequences. A novel and effective…