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awesome-video-domain-adaptation

A comprehensive collection of awesome research and other items about video domain adaptation
https://github.com/xuyu0010/awesome-video-domain-adaptation

Last synced: 2 days ago
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Closed-set VDA
- Unsupervised Video Domain Adaptation: A Disentanglement Perspective - PyTorch]](https://github.com/ldkong1205/TranSVAE) [[Project Page]](https://ldkong.com/TranSVAE)
- Synthetic-to-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performances - v2) [[ArXiv]](https://arxiv.org/abs/2303.10280)
- Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action Recognition
- Exploiting Instance-based Mixed Sampling via Auxiliary Source Domain Supervision for Domain-adaptive Action Detection
- Domain Adaptive Video Semantic Segmentation via Cross-Domain Moving Object Mixing
- Domain Adaptive Video Segmentation via Temporal Pseudo Supervision - PyTorch]](https://github.com/xing0047/TPS) (*Video Segmentation*)
- Audio-Adaptive Activity Recognition Across Video Domains - PyTorch]](https://github.com/xiaobai1217/DomainAdaptation) [[Project Page]](https://xiaobai1217.github.io/DomainAdaptation/)
- Interact before Align: Leveraging Cross-Modal Knowledge for Domain Adaptive Action Recognition - vision.org/publication/2022-yang-interact/)
- Multi-Level Attentive Adversarial Learning With Temporal Dilation for Unsupervised Video Domain Adaptation - PyTorch]](https://github.com/justchenpp/MA2L-TD)
- Dual-Head Contrastive Domain Adaptation for Video Action Recognition - PyTorch]](https://github.com/vturrisi/CO2A)
- Contrast and mix: Temporal contrastive video domain adaptation with background mixing - PyTorch]](https://github.com/CVIR/CoMix) [[Project Page]](https://cvir.github.io/projects/comix)
- Learning Cross-Modal Contrastive Features for Video Domain Adaptation
- Domain Adaptive Video Segmentation via Temporal Consistency Regularization - PyTorch]](https://github.com/Dayan-Guan/DA-VSN) (*Video Segmentation*)
- Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality Assessment - PyTorch]](https://github.com/cpf0079/UCDA) (*Video Quality Assessment (VQA)*)
- Spatio-temporal Contrastive Domain Adaptation for Action Recognition
- Unsupervised Domain Adaptation for Spatio-Temporal Action Localization
- Shuffle and Attend: Video Domain Adaptation
- Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation - PyTorch]](https://github.com/cmhungsteve/SSTDA) [[Project Page]](https://minhungchen.netlify.app/project/cdas/) (*Action Segmentation*)
- Transferring Cross-domain Knowledge for Video Sign Language Recognition
- Adversarial Cross-Domain Action Recognition with Co-Attention
- Generative Adversarial Networks for Video-to-Video Domain Adaptation
- Action Segmentation with Mixed Temporal Domain Adaptation
- Actor and Observer: Joint Modeling of First and Third-Person Videos - PyTorch]](https://github.com/gsig/actor-observer)
- Deep Domain Adaptation in Action Space
- Aligning Correlation Information for Domain Adaptation in Action Recognition
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Dynamic video mix-up for cross-domain action recognition - 368 (2022)
- A Novel Multiple-View Adversarial Learning Network for Unsupervised Domain Adaptation Action Recognition
- A Pairwise Attentive Adversarial Spatiotemporal Network for Cross-Domain Few-Shot Action Recognition-R2 - 782 (2020)
- Pairwise Two-Stream ConvNets for Cross-Domain Action Recognition With Small Data - 1161 (2020)
- Evaluation of local spatial–temporal features for cross-view action recognition - 117 (2016)
- Memory Efficient Temporal & Visual Graph Model for Unsupervised Video Domain Adaptation
- Channel-Temporal Attention for First-Person Video Domain Adaptation
- Unsupervised Domain Adaptation for Video Semantic Segmentation
- Temporal Attentive Alignment for Video Domain Adaptation - Pytorch]](https://github.com/cmhungsteve/TA3N) (Highly related to [TA3N]((http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_Temporal_Attentive_Alignment_for_Large-Scale_Video_Domain_Adaptation_ICCV_2019_paper.pdf)))
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Adversarial Cross-Domain Action Recognition with Co-Attention
- Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
- Channel-Temporal Attention for First-Person Video Domain Adaptation
Partial-set VDA
- Partial Video Domain Adaptation With Partial Adversarial Temporal Attentive Network - PyTorch]](https://github.com/xuyu0010/PATAN) [[Project Page]](https://xuyu0010.github.io/pvda.html)
Open-set VDA
Multi-Source VDA
- Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment
Source-Free or Test-time VDA
- The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation - PyTorch]](https://github.com/giaczara/dallv)
- Video Test-Time Adaptation for Action Recognition - PyTorch]](https://github.com/wlin-at/ViTTA) [[Supplementary]](https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lin_Video_Test-Time_Adaptation_CVPR_2023_supplemental.pdf)
- Source-Free Video Domain Adaptation with Spatial-Temporal-Historical Consistency Learning
- Overcoming Label Noise for Source-free Unsupervised Video Domain Adaptation
- Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition - PyTorch]](https://github.com/xuyu0010/ATCoN) [[Project Page]](https://xuyu0010.github.io/sfvda.html)
- Self-supervised Test-time Adaptation on Video Data
Target-Free VDA
- Cross-Domain Video Anomaly Detection without Target Domain Adaptation
Few-shot VDA
- Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
Continual VDA
- Confidence Attention and Generalization Enhanced Distillation for Continuous Video Domain Adaptation
Zero-shot VDA (Video Domain Generalization)
- Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition
- VideoDG: generalizing temporal relations in videos to novel domains
Other Topics in Video Transfer Learning
- CycDA: Unsupervised Cycle Domain Adaptation to Learn from Image to Video
- Benchmarking the robustness of Spatial-Temporal Models - TensorFlow]](https://github.com/Newbeeyoung/Video-Corruption-Robustness) (*Video Robustness*)
- Spatial-temporal causal inference for partial image-to-video adaptation - PyTorch]](https://github.com/ChenJinBIT/HPDA) (*Partial-Set Image-to-Video*)
- Image to Video Domain Adaptation Using Web Supervision - to-Video*)
- DistInit: Learning Video Representations Without a Single Labeled Video - to-Video*)
- Multi-Domain and Multi-Task Learning for Human Action Recognition - 867 (2019)
- Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition - 3182 (2019) [[Project Page]](https://yangliu9208.github.io/DIVAFN/) (*Image-to-Video*)
- Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action Recognition
- HMDB51 - source/kinetics), which are commonly used in these cross-domain video datasets.
- HMDB-ARID - and-download)
- Kinetics→NEC-Drone
- Charades-Ego
- MiniKinetics-UCF - set*)
- Daily-DA
Challenges for Video Domain Adaptation
- 5<sup>th</sup> UG2<sup>+</sup> Prize Challenge: Bridging the Gap Between Computational Photography and Visual Recognition (Track 2)
- Epic-Kitchens-100 2022 Challenge: Domain Adaptation for Action Recognition - computing.org/EPIC_CVPR22/)
Uncategorized
- Uncategorized
  - this DOI
Multi-Modal VDA
- Multi-Modal Continual Test-Time Adaptation for 3D Semantic Segmentation

Categories

Closed-set VDA 80 Other Topics in Video Transfer Learning 14 Source-Free or Test-time VDA 6 Open-set VDA 3 Zero-shot VDA (Video Domain Generalization) 2 Challenges for Video Domain Adaptation 2 Multi-Modal VDA 1 Multi-Source VDA 1 Partial-set VDA 1 Continual VDA 1 Few-shot VDA 1 Uncategorized 1 Target-Free VDA 1

Sub Categories

Uncategorized 1