Request to add papers

[xuyu0010]

Hi Yuejiang,

Thanks for maintaining this awesome list!

I would like to request to add our ECCV 2022 paper: "Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition" (URL: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136940144.pdf https://arxiv.org/abs/2203.04559) (Project URL: https://xuyu0010.github.io/sfvda.html). This is one of the pioneer works in source-free video domain adaptation (SFVDA) where we tackle the task by learning temporal consistency across local temporal features.

I would also like to request to add our Preprint paper: "Multi-Modal Continual Test-Time Adaptation for 3D Semantic Segmentation" (URL: https://arxiv.org/abs/2303.10457) where we explore Multi-Modal Continual Test-Time Adaptation (MM-CTTA) as a new extension of Continual Test-Time Adaptation (CTTA) for 3D semantic segmentation by adaptively attend to the reliable modality while avoiding catastrophic forgetting during continual domain shifts.

Thank you very much! Yuecong

[YuejiangLIU]

Hi Yuecong, thanks for sharing that! I've added your paper on Source-free Video Domain Adaptation to the list. I'd be happy to add the other, too, once it goes through peer review. Please keep me posted :)

[xuyu0010]

Hi Yuejiang,

Thank you very much for your reply! No problem, I will keep you posted when the other goes through peer review. I will close this issue for the time being and re-open it when the status of the paper on Multi-Modal Continual Test-Time Adaptation is updated in the future (near, hopefully).

Yuecong

[xuyu0010]

Hi Yuejiang,

I would like to update you that our paper has been accepted by ICCV 2023 and is now available at URL: https://openaccess.thecvf.com/content/ICCV2023/html/Cao_Multi-Modal_Continual_Test-Time_Adaptation_for_3D_Semantic_Segmentation_ICCV_2023_paper.html . I would like to re-request to add this paper into your repository. Thank you!

Yuecong