4 citations · 4 across the 6 of their papers we have counts for
6 papers
Guiding Diffusion Models with Semantically Degraded Conditions
Shilong Han, Yuming Zhang, Hongxia Wang
Classifier-Free Guidance (CFG) is a cornerstone of modern text-to-image models, yet its reliance on a semantically vacuous null prompt () generates a guidance signal p…
FedSCA: Federated Tuning with Similarity-guided Collaborative Aggregation for Heterogeneous Medical Image Segmentation
Yumin Zhang, Yan Gao, Haoran Duan +4
Transformer-based foundation models (FMs) have recently demonstrated remarkable performance in medical image segmentation. However, scaling these models is challenging due to the l…
Exemplar-condensed Federated Class-incremental Learning
Rui Sun, Yumin Zhang, Varun Ojha +4
We propose Exemplar-Condensed federated class-incremental learning (ECoral) to distil the training characteristics of real images from streaming data into informative rehearsal exe…
Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation
Yumin Zhang, Hongliu Li, Yajun Gao +3
Few-shot medical image segmentation has achieved great progress in improving accuracy and efficiency of medical analysis in the biomedical imaging field. However, most existing met…
ExactDreamer: High-Fidelity Text-to-3D Content Creation via Exact Score Matching
Yumin Zhang, Xingyu Miao, Haoran Duan +4
Text-to-3D content creation is a rapidly evolving research area. Given the scarcity of 3D data, current approaches often adapt pre-trained 2D diffusion models for 3D synthesis. Amo…
From Sora What We Can See: A Survey of Text-to-Video Generation
Rui Sun, Yumin Zhang, Tejal Shah +6
With impressive achievements made, artificial intelligence is on the path forward to artificial general intelligence. Sora, developed by OpenAI, which is capable of minute-level wo…