Search Results for author:
Found 9 papers, 6 papers with code
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains
We focus on scenarios where data distributions vary across multiple segments of the entire population and only make local assumptions about the differences between training and test (deployment) distributions within each segment.
TechGPT-2.0: A large language model project to solve the task of knowledge graph construction
Large language models have exhibited robust performance across diverse natural language processing tasks.
Continuous Pose for Monocular Cameras in Neural Implicit Representation
In this paper, we showcase the effectiveness of optimizing monocular camera poses as a continuous function of time.
Deformable Neural Radiance Fields using RGB and Event Cameras
In this work, we develop a novel method to model the deformable neural radiance fields using RGB and event cameras.
Fusing Monocular Images and Sparse IMU Signals for Real-time Human Motion Capture
We believe that the combination is complementary and able to solve the inherent difficulties of using one modality input, including occlusions, extreme lighting/texture, and out-of-view for visual mocap and global drifts for inertial mocap.
Ranked #1 on
3D Human Pose Estimation
on AIST++
An Understanding-Oriented Robust Machine Reading Comprehension Model
In this paper, we propose an understanding-oriented machine reading comprehension model to address three kinds of robustness issues, which are over sensitivity, over stability and generalization.
EMFlow: Data Imputation in Latent Space via EM and Deep Flow Models
The presence of missing values within high-dimensional data is an ubiquitous problem for many applied sciences.
Decoupled Self Attention for Accurate One Stage Object Detection
When DSA module and object confidence task are applied in RetinaNet together, the detection performances based on ResNet50 and ResNet101 can be increased by 1. 0% AP and 1. 4% AP respectively.
A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components
Estimating parameters of mixture model has wide applications ranging from classification problems to estimating of complex distributions.
