Search Results for author:
Found 2 papers, 0 papers with code
Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation
This paper addresses text-supervised semantic segmentation, aiming to learn a model capable of segmenting arbitrary visual concepts within images by using only image-text pairs without dense annotations.
An MIL-Derived Transformer for Weakly Supervised Point Cloud Segmentation
We address weakly supervised point cloud segmentation by proposing a new model, MIL-derived transformer, to mine additional supervisory signals.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
