Causal intervention for weakly-supervised semantic segmentation

• Main Authors: ZHANG Dong, ZHANG, Hanwang, TANG, Jinhui, HUA, Xian-Sheng, SUN, Qianru
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5597; https://ink.library.smu.edu.sg/context/sis_research/article/6600/viewcontent/NeurIPS_2020_causal_intervention_for_weakly_supervised_semantic_segmentation_Paper.pdf
• Institution: Singapore Management University

We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks t...