🏢 Xidian University

Satformer: a novel neural network accurately estimates satellite network traffic using an adaptive sparse spatio-temporal attention mechanism, outperforming existing methods.

SA3DIP boosts 3D instance segmentation accuracy by cleverly using 3D spatial and textural cues alongside 2D multi-view masks, overcoming limitations of previous methods.

Pretrained Optimization Model (POM) excels at zero-shot black-box optimization, outperforming existing methods, especially in high dimensions, through direct application or few-shot fine-tuning.

Peri-midFormer uses a novel periodic pyramid transformer to effectively model complex periodic variations in time series, achieving state-of-the-art results in forecasting, imputation, classification,…

New feature-level adversarial attacks disrupt visible-infrared person re-identification (VIReID) systems by cleverly aligning and manipulating features to cause incorrect ranking results.

E2E-MFD: A novel end-to-end multimodal fusion detection algorithm achieves state-of-the-art performance by synchronously optimizing image fusion and object detection.

E-Motion: Predicting future motion with unprecedented accuracy using event cameras and video diffusion models.

Unsupervised OOD detection gets a boost with a diffusion-based approach that leverages multi-layer semantic feature reconstruction for improved accuracy and speed.

SeCo: Semantic Connectivity-driven Pseudo-Labeling enhances cross-domain semantic segmentation by correcting noisy pseudo-labels at the connectivity level, improving model accuracy and robustness.

ACFun: A novel facial stylization method fusing abstract & concrete features for high-quality, artistically pleasing results from only one style & one face image.