Wei Lin

Orcid: 0000-0001-9213-5954

Affiliations:
  • Graz University of Technology, Austria


According to our database1, Wei Lin authored at least 13 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs.
CoRR, 2024

2023
AIRA-DA: Adversarial Image Reconstruction Alignments for Unsupervised Domain Adaptive Object Detection.
IEEE Robotics Autom. Lett., June, 2023

TAP: Targeted Prompting for Task Adaptive Generation of Textual Training Instances for Visual Classification.
CoRR, 2023

AIR-DA: Adversarial Image Reconstruction for Unsupervised Domain Adaptive Object Detection.
CoRR, 2023

LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

MATE: Masked Autoencoders are Online 3D Test-Time Learners.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering.
Proceedings of the 26th Computer Vision Winter Workshop (CVWW 2023), 2023

ActMAD: Activation Matching to Align Distributions for Test-Time-Training.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Video Test-Time Adaptation for Action Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
CycDA: Unsupervised Cycle Domain Adaptation from Image to Video.
CoRR, 2022

CycDA: Unsupervised Cycle Domain Adaptation to Learn from Image to Video.
Proceedings of the Computer Vision - ECCV 2022, 2022


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