Research Interests
The Machine Perception and Learning (MAPLE) Lab has long been engaged in artificial intelligence, especially deep learning and its research in generative Artificial intelligence (AIGC), multimodal understanding and generative large models, 2D/3D intelligent creation, virtual reality, etc. 1.Intelligent creation based on generative artificial intelligence, such as GAN model, diffusion model, self-coding model and other deep learning theory and application;2.Multi-modal understanding and generation direction: video and image multi-modal generation and editing, 2D/3D scene and human body perception, reconstruction and interaction;3.Theory and application of artificial intelligence in 2D/3D virtual content creation, especially automatic 2D/3D virtual reality object and scene generation, non-rigid object generation and driving model with human main object;
Meet The Team
Principle Investigator
Prof. Guo-Jun Qi was a technical VP and the Chief Scientist in Futurewei Technologies (Huawei Research America) based in Bellevue, WA, overseeing and leading the R&D for multiple cloud computing services, including Smart Cities, Visual Computing, Satellite Remoting Sensing, Vechicle Networking, and Autonomous Driving, and then founded the OPPO Research Center based in Seattle and several other cities across countries. He is a Changjiang Chair Professor at Westlake University, the first private non-profit research-oriented university based in Hangzhou. Previously, he was a faculty member and the director of MAPLE (MAchine Perception and LEarning) lab at Computer Science Department in the University of Central Florida, and a Research Staff Member at the IBM T.J. Watson Research Center (Yorktown Heights, NY). Before that, he worked in National University of Singapore and Microsoft Research Asia. He received Bachelor and Ph.D. degrees from the University of Science and Technology of China and the University of Illinois at Urbana-Champaign.
He is a Fellow of IEEE, IAPR and AAIA, as well as an ACM Distinguished Scientist and a Life Member of AAAI.
Group News
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Feb 27, 2025 Accepted by CVPR 2025
Our Paper "Schedule On the Fly: Diffusion Time Prediction for Faster and Better Image Generation" has been accepted by CVPR 2025. Congratulations to MAPLE Group!
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Dec 16, 2024 Published online:
Our Paper on “Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization” was accepted by ACM Multimedia 2024 as oral project, where we demonstrate that Equilibrated Diffusion surpasses other competitors with better subject consistency while closely adhering to text descriptions, thus validating the superiority of our approach
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Dec 16, 2024 Published online:
Our Paper on “One-Step Diffusion Distillation through Score Implicit Matching” was accepted by NeurIPS 2024, where we introduce the method “score implicit matching (SIM)”, which enables to transform pre-trained multi-step diffusion models into one-step generators in a data-free fashion
