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Computer Vision

Enabling computers and devices to understand what they see.

Microsoft at CVPR 2024: Innovations in computer vision and AI research

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Exploring how context, culture, and character matter in avatar research

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

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Published Date

Video

Deep Medicine: Leveraging AI for health in a relevant and impactful way in Africa

April 25, 2022 | Quentin Awori

The AI field is rife with advances in computer vision, natural language processing and innovation in their application to everyday life. Research in this area is at an all-time high. Does healthcare stand to benefit…

Deep Medicine: Leveraging AI for health in a relevant and impactful way in Africa

56:35

Publication

Debiased Learning from Naturally Imbalanced Pseudo-Labels

Xudong Wang, Zhirong Wu, Long Lian, Stella X. Yu

2022 Computer Vision and Pattern Recognition | April 2022

Publication

K-LITE: Learning Transferable Visual Models with External Knowledge

Sheng Shen, Chunyuan Li, Xiaowei Hu, Yujia Xie, Jianwei Yang, Pengchuan Zhang, Zhe Gan, Lijuan Wang, Lu Yuan, Ce Liu, Kurt Keutzer, Trevor Darrell, Anna Rohrbach, Jianfeng Gao

NeurIPS 2022 | April 2022

Oral Presentation (1%)

Project

Publication

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

Chunyuan Li, Haotian Liu, Liunian Harold Li, Pengchuan Zhang, Jyoti Aneja, Jianwei Yang, Ping Jin, Yong Jae Lee, Houdong Hu, Zicheng Liu, Jianfeng Gao

NeurIPS (Datasets and Benchmarks Track) | April 2022

Benchmark Page: https://computer-vision-in-the-wild.github.io/ELEVATER/

Publication