Comments (6)
Also looking forward to the codes of segmentation
from vida.
We are very interested in your article. However, we found that the link you provided is the Cotta method (Continual Test-Time Domain Adaptation), not the code corresponding to your article (VIDA: HOMEOSTATIC VISUAL DOMAIN ADAPTER FOR
CONTINUAL TEST TIME ADAPTATION). When will the segmentation code corresponding your article be releasesd?
from vida.
Thank you for your interest in our project. We intend to release our code once the paper has been accepted. You could download our segmentation codebase from here.
from vida.
@JimPlayboy Same here.
from vida.
Thank you for your interest in our work. We are in the process of organizing the code and plan to release it shortly after the deadline for ECCV 🙏 🙏 . If you urgently need our segmentation code in the next few days, please send an email to [email protected], and I will send you the core code privately (however, some variable names may not be standardized, and may be somewhat messy.).
from vida.
Official Notice: Thank you for your interest in our work. We open-sourced the code for CiFAR100-CiFAR100C yesterday (2024.04.15). For segmentation code, you can quickly integrate it by following CoTTA's segmentation code framework and ViDA method code. For example, you can utilize entire CoTTA's framework, which includes the dataloader, model creation, training code, and evaluation part, and inject our proposed method into the SegFormer model.
from vida.
Related Issues (14)
- Is the paper accepted to the NIPS? HOT 3
- Where are the codes of adapter? HOT 3
- Unfair comparison with CoTTA in segmentation tasks with lower learning rate HOT 8
- Adapter Code HOT 1
- question about adapter initialization for segmentation vida HOT 1
- About training vida source model HOT 15
- Source VIDA Model vs. Source Model HOT 2
- Request code and pretrained source vida model on Cifar100C & ACDC HOT 1
- labels between cifar100 and cifar100c HOT 1
- About Gradient Problem and Resnet Model HOT 1
- ViDA's results on ResNet50+ImageNet-C
- Pretrained ViDA Model and Code for ResNet-50
- About the transformation of ImageNet dataset for ViT base model
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from vida.