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 at segmenting the incremental new classes without losing the ability on old classes. Currently, some CISS methods based on feature knowledge distillation suffer from the stability-plasticity dilemma,i.e., excessive knowledge distillation may impede ...
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 ...
Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation Link to our Paper:https://arxiv.org/abs/2308.02790 Prerequisites and Requirements We tested our code under Ubuntu 20.04 and Windows with - Python 3.11.4 - Cuda 11.8 - PyTorch 2.0.1 ...
21 p. How far can we go with ImageNet for Text-to-Image generation? 27 p. Assessing zero-shot generalisation behaviour in graph-neural-network interatomic potentials 6 p. Doping dependence of 2-spinon excitations in the doped 1D cuprate Ba$_2$CuO$_{3+delta}$ 19 p. Identifying ...
[22] Jungbeom Lee, Eunji Kim, and Sungroh Yoon.Antiadversarially Manipulated Attributions for Weakly and Semisupervised Semantic Segmentation. CVPR, 2021. 双层优化问题(Bilevel Optimization Problems, BOP) BOP旨在解决嵌套优化问题,其中外层优化依赖于内层优化的结果。BOP在超参数选择 [29] 和元学习 [13]...
We consider a class-incremental semantic segmentation (CISS) problem. While\nsome recently proposed algorithms utilized variants of knowledge distillation\n(KD) technique to tackle the problem, they only partially addressed the key\naddi... S Cha,B Kim,Y Yoo,... 被引量: 0发表: 2021年 加载更...
[16] proposes feature-level knowledge distillation when applying continual learning [37] into semantic segmentation task [53, 52, 11]. Rehearsal Strategy: For replaying past experience, lots of CIL methods [49, 8, 42] allocate a memory to store ex- emplars of old...
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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 (...