91 citations · 155 across the 30 of their papers we have counts for
4 papers · 1 filter
Spectral Prompt Tuning:Unveiling Unseen Classes for Zero-Shot Semantic Segmentation
Wenhao Xu, Rongtao Xu, Changwei Wang +4
Recently, CLIP has found practical utility in the domain of pixel-level zero-shot segmentation tasks. The present landscape features two-stage methodologies beset by issues such as…
Advances in Embodied Navigation Using Large Language Models: A Survey
Jinzhou Lin, Han Gao, Xuxiang Feng +5
In recent years, the rapid advancement of Large Language Models (LLMs) such as the Generative Pre-trained Transformer (GPT) has attracted increasing attention due to their potentia…
Segment Anything Model is a Good Teacher for Local Feature Learning
Jingqian Wu, Rongtao Xu, Zach Wood-Doughty +3
Local feature detection and description play an important role in many computer vision tasks, which are designed to detect and describe keypoints in "any scene" and "any downstream…
Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation
Rongtao Xu, Changwei Wang, Jiaxi Sun +3
Efficiently training accurate deep models for weakly supervised semantic segmentation (WSSS) with image-level labels is challenging and important. Recently, end-to-end WSSS methods…