4 papers · 1 filter
MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension
Ting Liu, Zunnan Xu, Yue Hu +3
Referring Expression Comprehension (REC), which aims to ground a local visual region via natural language, is a task that heavily relies on multimodal alignment. Most existing meth…
M2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension
Xuyang Liu, Ting Liu, Siteng Huang +6
Referring expression comprehension (REC) is a vision-language task to locate a target object in an image based on a language expression. Fully fine-tuning general-purpose pre-train…
DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding
Ting Liu, Xuyang Liu, Siteng Huang +5
Visual grounding (VG) is a challenging task to localize an object in an image based on a textual description. Recent surge in the scale of VG models has substantially improved perf…
Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning and Inference
Ting Liu, Xuyang Liu, Liangtao Shi +6
Parameter-efficient fine-tuning (PEFT) has emerged as a popular solution for adapting pre-trained Vision Transformer (ViT) models to downstream applications by updating only a smal…