5 citations · 8 across the 6 of their papers we have counts for
6 papers
Decouple before Align: Visual Disentanglement Enhances Prompt Tuning
Fei Zhang, Tianfei Zhou, Jiangchao Yao +3
Prompt tuning (PT), as an emerging resource-efficient fine-tuning paradigm, has showcased remarkable effectiveness in improving the task-specific transferability of vision-language…
ConText: Driving In-context Learning for Text Removal and Segmentation
Fei Zhang, Pei Zhang, Baosong Yang +3
This paper presents the first study on adapting the visual in-context learning (V-ICL) paradigm to optical character recognition tasks, specifically focusing on text removal and se…
G4Seg: Generation for Inexact Segmentation Refinement with Diffusion Models
Tianjiao Zhang, Fei Zhang, Jiangchao Yao +2
This paper considers the problem of utilizing a large-scale text-to-image diffusion model to tackle the challenging Inexact Segmentation (IS) task. Unlike traditional approaches th…
Audio-Visual Segmentation via Unlabeled Frame Exploitation
Jinxiang Liu, Yikun Liu, Fei Zhang +3
Audio-visual segmentation (AVS) aims to segment the sounding objects in video frames. Although great progress has been witnessed, we experimentally reveal that current methods reac…
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
Fei Zhang, Tianfei Zhou, Boyang Li +6
This paper studies the problem of weakly open-vocabulary semantic segmentation (WOVSS), which learns to segment objects of arbitrary classes using mere image-text pairs. Existing w…
AttrSeg: Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation
Chaofan Ma, Yuhuan Yang, Chen Ju +3
Open-vocabulary semantic segmentation is a challenging task that requires segmenting novel object categories at inference time. Recent studies have explored vision-language pre-tra…