4 papers
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models
Jiayu Li, Jiaxin Qi, Sheng Zhou +2
Contrastive vision-language models like CLIP exhibit remarkable zero-shot generalization. However, prompt tuning remains highly sensitive to label noise, as mislabeled samples gene…
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning
Jiaqi Huang, Zunnan Xu, Jun Zhou +6
Leveraging multimodal large models for image segmentation has become a prominent research direction. However, existing approaches typically rely heavily on manually annotated datas…
Separate to Collaborate: Dual-Stream Diffusion Model for Coordinated Piano Hand Motion Synthesis
Zihao Liu, Mingwen Ou, Zunnan Xu +4
Automating the synthesis of coordinated bimanual piano performances poses significant challenges, particularly in capturing the intricate choreography between the hands while prese…
Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation
Jiaqi Huang, Zunnan Xu, Ting Liu +4
In the domain of computer vision, Parameter-Efficient Tuning (PET) is increasingly replacing the traditional paradigm of pre-training followed by full fine-tuning. PET is particula…