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publications
MindPainter: Efficient Brain-Conditioned Painting of Natural Images via Cross-Modal Self-Supervised Learning
Published in The 39th Annual AAAI Conference on Artificial Intelligence 2024, 2024
This paper proposes MindPainter, a method for efficient brain-conditioned image editing using brain signals of visual perception as prompts. By employing cross-modal self-supervised learning, it directly reconstructs masked images with pseudo-brain signals generated by the Pseudo Brain Generator, enabling seamless cross-modal integration. The Brain Adapter ensures accurate interpretation of brain signals, while the Multi-Mask Generation Policy enhances generalization for high-quality editing in various scenarios, such as inpainting and outpainting. MindPainter is the first to achieve efficient brain-conditioned image painting, advancing direct brain control in creative AI.
Recommended citation: Muzhou Yu, Shuyun Lin, Hongwei Yan, Kaisheng Ma*. "MindPainter: Efficient Brain-Conditioned Painting of Natural Images via Cross-Modal Self-Supervised Learning." The 39th Annual AAAI Conference on Artificial Intelligence 2024 https://arxiv.org/pdf/xxxx.xxxxx
Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024, 2024
This paper is about our proposed online continual learning algorithm MOSE, which is inspired by the multi-level feature extraction and cross-layer communication inherent to animal neural circuits, aiming to enhance the model's adaptivity to dynamic distributions and resistance against forgetting.
Recommended citation: Hongwei Yan, Liyuan Wang*, Kaisheng Ma*, and Yi Zhong*. "Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation." IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 https://arxiv.org/pdf/2404.00417
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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