Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation Dipam Goswami†§ Rene´ Schuster† Joost van de Weijer‡ Didier Stricker† dipamgoswami01@gmail.com rene.schuster@dfki.de joost@...
Class-Incremental Semantic Segmentation (CISS) aims to learn new classes without forgetting the old ones, using only the labels of the new classes. To achieve this, two popular strategies are employed: 1) pseudo-labeling and knowledge distillation to preserve prior knowledge; and 2) background ...
train_erfnet_incremental.py new file: .gitignore Aug 8, 2023 train_erfnet_static.py new file: .gitignore Aug 8, 2023 Repository files navigation README License Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation ...
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As a front-burner problem in incremental learning, class incremental semantic segmentation (CISS) is plagued by catastrophic forgetting and semantic drift. Although recent methods have utilized knowledge distillation to transfer knowledge from the old model, they are still unable to avoid pixel confusion...
Luo Z, Liu Y, Schiele B, et al. Class-incremental exemplar compression for class-incremental learning[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023: 11371-11380. 在类增量学习中,模型需要在有限的内存预算下,保存旧类别的示例(exemplars),并不断学习新类...
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk1,2,3,∗ Joost van de Weijer4,5 Bartosz Zielin´ski1,3,6 Bartłomiej Twardowski4,5,6 1 Faculty of Mathematics and Computer Science, Jagiellonian University 2 Doctoral School of Exact and Life Sci...
The Filter Bank Networks consistently outperform the baselines while using significantly fewer learnable parameters, demonstrating the strong generalization ability of filter banks to the unseen variants of semantic patterns. 4.2. Few-Shot Class-Incremental Learning We evaluate the proposed FBN on the comm...
将class incremental learning转化为task incremental learning,每个task相当于为每个标签y学一个类别条件生成模型。 Method 作者使用VAE作为每个类别要学习的生成式分类器,通过重要性采样估计似然p(x|y)p(x|y),使用均匀分布建模p(y)p(y)。 VAE包含一个encoderqϕqϕ,将输入变为隐空间的后验分布qϕ(z|x)...
This is an official implementation of the paper "Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation", accepted by NeurIPS 2023. [paper]InstallationPre-requisitesThis repository has been tested with the following environment:CUDA (...