38 citations · 41 across the 11 of their papers we have counts for
5 papers · 1 filter
SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP
Yusuke Hirota, Min-Hung Chen, Chien-Yi Wang +3
Large-scale vision-language models, such as CLIP, are known to contain societal bias regarding protected attributes (e.g., gender, age). This paper aims to address the problems of…
GroPrompt: Efficient Grounded Prompting and Adaptation for Referring Video Object Segmentation
Ci-Siang Lin, I-Jieh Liu, Min-Hung Chen +3
Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence throughout the entire video. Most existing methods require end-to-end traini…
MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypes
Bor-Shiun Wang, Chien-Yi Wang, Wei-Chen Chiu
Recent advancements in post-hoc and inherently interpretable methods have markedly enhanced the explanations of black box classifier models. These methods operate either through po…
DoRA: Weight-Decomposed Low-Rank Adaptation
Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin +4
Among the widely used parameter-efficient fine-tuning (PEFT) methods, LoRA and its variants have gained considerable popularity because of avoiding additional inference costs. Howe…
Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
Ci-Siang Lin, Chien-Yi Wang, Yu-Chiang Frank Wang +1
Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models using image data with only image-level supervision. Since precise pixel-level annotations are not a…