3 accepted papers
Sign language processing has traditionally relied on task-specific models, limiting the potential for transfer learning across tasks. Pre-training methods for sign language have typically focused on either supervised pre-training, which cannot take advantage of unlabeled data, or context-independent…
A persistent challenge in sign language video processing, including the task of sign language to written language translation, is how we train efficient model given the nature of videos. Informed by the nature and linguistics of signed languages, our proposed method focuses on just the most relevant…
A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the Jacobian of a differentiable renderer, which we instantiate to be a voxel radiance field. This setup aggregates 2D s…