PLUS Group @ ShanghaiTech

Perception, Learning and UnderStanding (PLUS): The research of our group is primarily focused on representation learning, including weakly-supervised learning and model generalization under small samples and/or multiple tasks, and complex reasoning for multimodal structured data in visual perception, natural language and bioinformatics.

PLUS Group @ ShanghaiTech

Perception, Learning and UnderStanding (PLUS): The research of our group is primarily focused on representation learning, including weakly-supervised learning and model generalization under small samples and/or multiple tasks, and complex reasoning for multimodal structured data in visual perception, natural language and bioinformatics.

PLUS Group @ ShanghaiTech

Perception, Learning and UnderStanding (PLUS): The research of our group is primarily focused on representation learning, including weakly-supervised learning and model generalization under small samples and/or multiple tasks, and complex reasoning for multimodal structured data in visual perception, natural language and bioinformatics.

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Join PLUS

🚩 We are recruiting undergrad students in SIST as Research Assistant for our projects. Click for more information.

🚩 Our group is also recruiting top-caliber graduate students with strong expertise in computer vision and machine learning for 2023. Please send email to Prof. Xuming He for more information after registering your application on the school website.

News

📌 [03/2024] Two papers accepted by CVPR 2024!

📌 [12/2023] One paper accepted by TPAMI 2023!

📌 [06/2022] One paper accepted by TMLR 2023!

📌 [06/2022] Two papers accepted by ICCV 2023!

📌 [06/2022] One paper accepted by IJCAI 2023!

📌 [06/2022] One paper accepted by CVPR 2023!

📌 [06/2022] Two papers accepted by ICLR 2023!

📌 [06/2022] One paper accepted by AAAI 2023!

📌 [06/2022] One paper accepted by FG 2023 as Best Student Paper!

Recent Publications

Quickly discover relevant content by filtering publications.

Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
In CVPR 2024.
PDF Code
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning

From Pixels to Graphs: Open-Vocabulary Scene Graph Generation with Vision-Language Models

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
In CVPR 2024.
PDF Code
From Pixels to Graphs: Open-Vocabulary Scene Graph Generation with Vision-Language Models

SGTR+: End-to-end Scene Graph Generation with Transformer

Scene Graph Generation (SGG) remains a challenging visual understanding task due to its compositional property. Most previous works …
In TPAMI 2023.
PDF Code
SGTR+: End-to-end Scene Graph Generation with Transformer
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Contact

  • 201210 Shanghai Pudong Zhangjiang Campus:393 Middle Huaxia Road
  • SIST Building No.1 and take the stairs to Office 311 on Floor 3