3 papers
cs.CV2024
Learning from the Web: Language Drives Weakly-Supervised Incremental Learning for Semantic Segmentation
Chang Liu, Giulia Rizzoli, Pietro Zanuttigh +2
Current weakly-supervised incremental learning for semantic segmentation (WILSS) approaches only consider replacing pixel-level annotations with image-level labels, while the train…
cs.CV2023
Retinex-guided Channel-grouping based Patch Swap for Arbitrary Style Transfer
Chang Liu, Yi Niu, Mingming Ma +2
The basic principle of the patch-matching based style transfer is to substitute the patches of the content image feature maps by the closest patches from the style image feature ma…
cs.CV2023
RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation
Chang Liu, Giulia Rizzoli, Francesco Barbato +5
Catastrophic forgetting of previous knowledge is a critical issue in continual learning typically handled through various regularization strategies. However, existing methods strug…