Search Results for author:
Found 6 papers, 3 papers with code
Against The Achilles' Heel: A Survey on Red Teaming for Generative Models
Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safety issues as various vulnerabilities are exposed.
D3Former: Jointly Learning Repeatable Dense Detectors and Feature-enhanced Descriptors via Saliency-guided Transformer
Notably, tests on 3DLoMatch, even with a low overlap ratio, show that our method consistently outperforms recently published approaches such as RoReg and RoITr.
UTBoost: A Tree-boosting based System for Uplift Modeling
Uplift modeling refers to the set of machine learning techniques that a manager may use to estimate customer uplift, that is, the net effect of an action on some customer outcome.
OAAFormer: Robust and Efficient Point Cloud Registration Through Overlapping-Aware Attention in Transformer
On one hand, we introduce a soft matching mechanism, facilitating the propagation of potentially valuable correspondences from coarse to fine levels.
Laplacian2Mesh: Laplacian-Based Mesh Understanding
Geometric deep learning has sparked a rising interest in computer graphics to perform shape understanding tasks, such as shape classification and semantic segmentation.
Neural-IMLS: Self-supervised Implicit Moving Least-Squares Network for Surface Reconstruction
We conducted extensive experiments on various benchmarks, including synthetic scans and real scans.
