16 citations · 37 across the 12 of their papers we have counts for
13 papers
Decoding Visual Neural Representations by Multimodal with Dynamic Balancing
Kaili sun, Xingyu Miao, Bing Zhai +2
In this work, we propose an innovative framework that integrates EEG, image, and text data, aiming to decode visual neural representations from low signal-to-noise ratio EEG signal…
Towards Scalable Spatial Intelligence via 2D-to-3D Data Lifting
Xingyu Miao, Haoran Duan, Quanhao Qian +6
Spatial intelligence is emerging as a transformative frontier in AI, yet it remains constrained by the scarcity of large-scale 3D datasets. Unlike the abundant 2D imagery, acquirin…
TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency
Minye Shao, Xingyu Miao, Haoran Duan +7
3D medical image generation is essential for data augmentation and patient privacy, calling for reliable and efficient models suited for clinical practice. However, current methods…
Rethinking Score Distilling Sampling for 3D Editing and Generation
Xingyu Miao, Haoran Duan, Yang Long +1
Score Distillation Sampling (SDS) has emerged as a prominent method for text-to-3D generation by leveraging the strengths of 2D diffusion models. However, SDS is limited to generat…
Attention in Diffusion Model: A Survey
Litao Hua, Fan Liu, Jie Su +9
Attention mechanisms have become a foundational component in diffusion models, significantly influencing their capacity across a wide range of generative and discriminative tasks.…
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…
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…
Wearable-based behaviour interpolation for semi-supervised human activity recognition
Haoran Duan, Shidong Wang, Varun Ojha +5
While traditional feature engineering for Human Activity Recognition (HAR) involves a trial-anderror process, deep learning has emerged as a preferred method for high-level represe…
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…
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…
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…