Papers with Code 아카이브

Test-time Adaptation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/donghao51/simmmdg

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models

https://github.com/haomo-ai/superfusion

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models

https://github.com/hhhaaahhhaa/asr-tta

Continual Test-time Adaptation for End-to-end Speech Recognition on Noisy Speech

https://github.com/iemprog/mimi

Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time Adaptation

https://github.com/kadmkbl/SURGEON

SURGEON: Memory-Adaptive Fully Test-Time Adaptation via Dynamic Activation Sparsity

https://github.com/mihirp1998/Diffusion-TTA

Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback

https://github.com/natureyoo/continualtta_objectdetection

What, How, and When Should Object Detectors Update in Continually Changing Test Domains?

https://github.com/neerakara/TTA_prostate

Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation

https://github.com/nigelyaoj/self-supervised-amodal-video-object-segmentation

Self-supervised Amodal Video Object Segmentation

https://github.com/prabhuteja12/pest

Test time Adaptation through Perturbation Robustness

https://github.com/tiangexiang/CurveNet

Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

https://github.com/zchuning/repo

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.