An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation Problems

2 May 2023

Papers citing "An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation Problems"

8 / 8 papers shown

Title
WPS-SAM: Towards Weakly-Supervised Part Segmentation with Foundation Models Xin-Jian Wu Rui-Song Zhang Jie Qin Shijie Ma Cheng-Lin Liu VLM 29 1 0 14 Jul 2024
Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation Ci-Siang Lin Chien-Yi Wang Yu-Chiang Frank Wang Min-Hung Chen VLM 21 0 0 22 Jan 2024
A Comprehensive Survey on Segment Anything Model for Vision and Beyond Chunhui Zhang Li Liu Yawen Cui Guanjie Huang Weilin Lin Yiqian Yang Yuehong Hu VLM 32 90 0 14 May 2023
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 390 4,125 0 28 Jan 2022
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentation Weixuan Sun Jing Zhang Zheyuan Liu Yiran Zhong Nick Barnes ViT 58 14 0 06 Dec 2021
Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast Ye Du Zehua Fu Qingjie Liu Yunhong Wang 87 129 0 14 Oct 2021
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation Jungbeom Lee Jooyoung Choi J. Mok Sungroh Yoon SSeg 210 134 0 13 Oct 2021
Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation Jiwoon Ahn Suha Kwak 220 740 0 28 Mar 2018