Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data

Author:

Mishra Samarth1,Panda Rameswar2,Phoo Cheng Perng3,Chen Chun-Fu Richard2,Karlinsky Leonid2,Saenko Kate1,Saligrama Venkatesh1,Feris Rogerio S.2

Affiliation:

1. Boston University

2. MIT-IBM Watson AI Lab

3. Cornell University

Publisher

IEEE

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Synthetic Data for Deep Learning in Computer Vision & Medical Imaging: A Means to Reduce Data Bias;ACM Computing Surveys;2024-06-28

2. Mixing synthetic and real data to build AI vision models;Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II;2024-06-07

3. PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

4. Self-Supervised Underwater Image Generation for Underwater Domain Pre-Training;IEEE Transactions on Instrumentation and Measurement;2024

5. From Pixels to Power: Critical Feminist Questions for the Ethics of Computer Vision;Modeling Visual Aesthetics, Emotion, and Artistic Style;2023-11-25

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