29 citations · 65 across the 9 of their papers we have counts for
9 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…
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…
Sentinel-Guided Zero-Shot Learning: A Collaborative Paradigm without Real Data Exposure
Fan Wan, Xingyu Miao, Haoran Duan +3
With increasing concerns over data privacy and model copyrights, especially in the context of collaborations between AI service providers and data owners, an innovative SG-ZSL para…
ConRF: Zero-shot Stylization of 3D Scenes with Conditioned Radiation Fields
Xingyu Miao, Yang Bai, Haoran Duan +4
Most of the existing works on arbitrary 3D NeRF style transfer required retraining on each single style condition. This work aims to achieve zero-shot controlled stylization in 3D…
CTNeRF: Cross-Time Transformer for Dynamic Neural Radiance Field from Monocular Video
Xingyu Miao, Yang Bai, Haoran Duan +4
The goal of our work is to generate high-quality novel views from monocular videos of complex and dynamic scenes. Prior methods, such as DynamicNeRF, have shown impressive performa…
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume
Xingyu Miao, Yang Bai, Haoran Duan +5
Self-supervised monocular depth estimation methods typically rely on the reprojection error to capture geometric relationships between successive frames in static environments. How…
Absolute Zero-Shot Learning
Rui Gao, Fan Wan, Daniel Organisciak +6
Considering the increasing concerns about data copyright and privacy issues, we present a novel Absolute Zero-Shot Learning (AZSL) paradigm, i.e., training a classifier with zero r…
Semi-Supervised Crowd Counting from Unlabeled Data
Haoran Duan, Fan Wan, Rui Sun +6
Automatic Crowd behavior analysis can be applied to effectively help the daily transportation statistics and planning, which helps the smart city construction. As one of the most i…