UnrealEgo: A New Dataset for Robust Egocentric 3D Human Motion Capture ECCV, 2022 |
SNUG: Self-Supervised Neural Dynamic Garments CVPR, 2022 |
Computer Vision strives to develop algorithms for understanding, interpreting and reconstructing information about real-world scenes from image and video data.
Computer Graphics focuses on image synthesis: algorithms to build and edit static and dynamic virtual worlds and to display them in photorealistic or stylized ways.
Machine Learning is concerned with studying and developing algorithms which use statistical models to solve problems by analyzing and drawing inference from data.
In recent years, these fields have converged more and more. Both Computer Vision and Computer Graphics create and exploit models describing the visual appearance of objects and scenes, while the most successful models heavily utilize ideas from Machine Learning. In this seminar series, we will cover advanced research topics that cross the boundaries between the fields of Computer Vision, Computer Graphics, and Machine Learning. This seminar will cover research papers from the following topics:
The following table lists more topics than available weeks – this is to allow some flexibility for the interests of the group to change the course structure. Once every participant has submitted their choice of topics, this list will be updated to show the presenter of each topic. Send us an email if you cannot access a paper for some reason.
Click on each topic to show the papers to be discussed or show all papers .
Topic and Papers | Presentation |
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SIGGRAPH Asia 2022
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Presenter:
Xiaojie
Supervisor:
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ECCV 2022
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Presenter:
Parham
Supervisor:
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ECCV 2020
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Presenter:
Ayce
Supervisor:
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Presenter:
Vedant
Supervisor:
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arXiv 2022
NeurIPS 2022
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Presenter:
Qinyuan
Supervisor:
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ACM ToG 2021
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Presenter:
Mohamed Ovais
Supervisor:
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arXiv 2022
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Presenter:
Celine
Supervisor:
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Presenter:
Andria
Supervisor:
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Presenter:
Shreyas
Supervisor:
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NeurIPS 2022
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Presenter:
Chinmay
Supervisor:
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Presenter:
Amala
Supervisor:
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Presenter:
Theophilus
Supervisor:
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