15 citations · 19 across the 9 of their papers we have counts for
10 papers
FMDConv: Fast Multi-Attention Dynamic Convolution via Speed-Accuracy Trade-off
Tianyu Zhang, Fan Wan, Haoran Duan +3
Spatial convolution is fundamental in constructing deep Convolutional Neural Networks (CNNs) for visual recognition. While dynamic convolution enhances model accuracy by adaptively…
D2Fusion: Dual-domain Fusion with Feature Superposition for Deepfake Detection
Xueqi Qiu, Xingyu Miao, Fan Wan +5
Deepfake detection is crucial for curbing the harm it causes to society. However, current Deepfake detection methods fail to thoroughly explore artifact information across differen…
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…
Asynchronous Personalized Federated Learning through Global Memorization
Fan Wan, Yuchen Li, Xueqi Qiu +6
The proliferation of Internet of Things devices and advances in communication technology have unleashed an explosion of personal data, amplifying privacy concerns amid stringent re…
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…
Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks
Zhenyu Liu, Haoran Duan, Huizhi Liang +5
Adversarial training is one of the most effective methods for enhancing model robustness. Recent approaches incorporate adversarial distillation in adversarial training architectur…
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…
Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score Matching
Xingyu Miao, Haoran Duan, Varun Ojha +4
In this work, we propose a novel Trajectory Score Matching (TSM) method that aims to solve the pseudo ground truth inconsistency problem caused by the accumulated error in Interval…
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…
Rehearsal-free Federated Domain-incremental Learning
Rui Sun, Haoran Duan, Jiahua Dong +3
We introduce a rehearsal-free federated domain incremental learning framework, RefFiL, based on a global prompt-sharing paradigm to alleviate catastrophic forgetting challenges in…