1 citations · 3 across the 7 of their papers we have counts for
9 papers · 1 filter
Multi-Task Label Discovery via Hierarchical Task Tokens for Partially Annotated Dense Predictions
Jingdong Zhang, Hanrong Ye, Xin Li +2
In recent years, simultaneous learning of multiple dense prediction tasks with partially annotated label data has emerged as an important research area. Previous works primarily fo…
X-VILA: Cross-Modality Alignment for Large Language Model
Hanrong Ye, De-An Huang, Yao Lu +8
We introduce X-VILA, an omni-modality model designed to extend the capabilities of large language models (LLMs) by incorporating image, video, and audio modalities. By aligning mod…
DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data
Hanrong Ye, Dan Xu
Recently, there has been an increased interest in the practical problem of learning multiple dense scene understanding tasks from partially annotated data, where each training samp…
SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis
Hanrong Ye, Jason Kuen, Qing Liu +3
We propose SegGen, a highly-effective training data generation method for image segmentation, which pushes the performance limits of state-of-the-art segmentation models to a signi…
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Experts
Hanrong Ye, Dan Xu
Learning discriminative task-specific features simultaneously for multiple distinct tasks is a fundamental problem in multi-task learning. Recent state-of-the-art models consider d…
Contrastive Multi-Task Dense Prediction
Siwei Yang, Hanrong Ye, Dan Xu
This paper targets the problem of multi-task dense prediction which aims to achieve simultaneous learning and inference on a bunch of multiple dense prediction tasks in a single fr…