Search Results for author:
Found 3 papers, 2 papers with code
Attention-guided Feature Distillation for Semantic Segmentation
In contrast to existing complex methodologies commonly employed for distilling knowledge from a teacher to a student, this paper showcases the efficacy of a simple yet powerful method for utilizing refined feature maps to transfer attention.
Leveraging Swin Transformer for Local-to-Global Weakly Supervised Semantic Segmentation
In recent years, weakly supervised semantic segmentation using image-level labels as supervision has received significant attention in the field of computer vision.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
AICSD: Adaptive Inter-Class Similarity Distillation for Semantic Segmentation
With inference time being a crucial factor, particularly in dense prediction tasks such as semantic segmentation, knowledge distillation has emerged as a successful technique for improving the accuracy of lightweight student networks.
