L2g: A simple local-to-global knowledge transfer framework for weakly supervised semantic segmentation
Mining precise class-aware attention maps, aka, class activation maps, is essential for
weakly supervised semantic segmentation. In this paper, we present L2G, a simple online …
weakly supervised semantic segmentation. In this paper, we present L2G, a simple online …
Multi-granularity denoising and bidirectional alignment for weakly supervised semantic segmentation
Weakly supervised semantic segmentation (WSSS) models relying on class activation maps
(CAMs) have achieved desirable performance comparing to the non-CAMs-based …
(CAMs) have achieved desirable performance comparing to the non-CAMs-based …
Weaksam: Segment anything meets weakly-supervised instance-level recognition
Weakly-supervised visual recognition using inexact supervision is a critical yet challenging
learning problem. It significantly reduces human labeling costs and traditionally relies on …
learning problem. It significantly reduces human labeling costs and traditionally relies on …
Subclassified loss: Rethinking data imbalance from subclass perspective for semantic segmentation
Semantic segmentation plays a crucial role in enabling intelligent vehicles to perceive and
understand their surroundings. However, datasets used for semantic segmentation often …
understand their surroundings. However, datasets used for semantic segmentation often …
Learning cross-channel representations for semantic segmentation
L Ma, H ** augmentation method for weakly supervised building extraction from high-resolution remote sensing imagery
It is time-consuming to collect a huge number of pixel-level annotations for accurately
extracting buildings by deep neural networks. Supported by class activation map (CAM) …
extracting buildings by deep neural networks. Supported by class activation map (CAM) …
Boosting Weakly-Supervised Image Segmentation via Representation, Transform, and Compensator
Weakly-supervised image segmentation (WSIS) is a fundamental task in the domain of
computer vision that relies on image-level class labels. While multi-stage training …
computer vision that relies on image-level class labels. While multi-stage training …