Research talks: Generalization and adaptation
The limitations of big data-driven deep learning in scalability and adaptation to real-world scenarios hinder its practical applications. To address these limitations, it’s extremely important to develop architectures and algorithms that can capture the fundamentals of how humans learn, infer, and reason. Join Professor Suha Kwak from POSTECH, Microsoft Principal Researcher Chong Luo, and Microsoft Principal Research Manager Lu Yuan as they discuss the theory and practice of unsupervised visual representation learning for 3D point clouds, videos, and images, which help address model generalization and adaptation to new data domains and new downstream tasks.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
- Track:
- Towards Human-Like Visual Learning & Reasoning
- Date:
- Speakers:
- Suha Kwak, Chong Luo, Lu Yuan
- Affiliation:
- POSTECH, Microsoft Research Asia, Microsoft
Towards Human-Like Visual Learning & Reasoning
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Opening remarks: Towards Human-Like Visual Learning and Reasoning
Speakers:- Wenjun Zeng,
- Wenjun Zeng
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Research talks: Learning for interpretability
Speakers:- Yuwang Wang,
- Hanwang Zhang,
- Shujian Yu
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Research talks: Few-shot and zero-shot visual learning and reasoning
Speakers:- Han Hu,
- Zhe Gan,
- Kyoung Mu Lee
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