Lei Xie

Seeing Semantic Shift: Difference-Aware Sentence-Level Temporal Segmentation of Sign Language Videos

Recent advances in sign language understanding have achieved impressive success on short, single-sentence videos, yet their performance drops sharply when applied to long, continuous sign language videos. To bridge this gap, we focus on a challenging and realistic setting: Visual-only Sentence-level Sign Language Segme...

Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Production

Uni-SLTP is proposed, a unified framework for SLT and SLP with two key components: a shared sign tokenizer that converts sign sequences into discrete tokens and latent representations, capturing both semantic and reconstructive information.

Sign Language Question Answering: A New Task, Benchmark, and Baseline for Sign Language Understanding

A new task, Sign Language Question Answering (SLQA), which evaluates SL understanding by requiring models to answer arbitrary natural language questions about SL videos, and a simple yet effective baseline model equipped with a Question-Conditioned Modulated Temporal Downsampling module and an in-domain knowledge trans...

Learning Effective Sign Features without Text for Gloss-free Sign Language Translation