Search Results for author:
Found 12 papers, 2 papers with code
DeClotH: Decomposable 3D Cloth and Human Body Reconstruction from a Single Image
Most existing methods of 3D clothed human reconstruction from a single image treat the clothed human as a single object without distinguishing between cloth and human body.
Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
In minimax optimization, the extragradient (EG) method has been extensively studied because it outperforms the gradient descent-ascent method in convex-concave (C-C) problems.
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Images
Compared to previous implicit-function-based methods, the point cloud diffusion model can capture the global consistent features to generate the occluded regions, and the denoising process corrects the misaligned SMPL meshes.
Dense Hand-Object(HO) GraspNet with Full Grasping Taxonomy and Dynamics
Accurate hand and object 3D meshes are obtained by fitting the hand parametric model (MANO) and the hand implicit function (HALO) to multi-view RGBD frames, with the MoCap system only for objects.
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
With a simple argument, we obtain optimal or best-known complexity guarantees with cohypomonotonicity or weak MVI conditions for $\rho < \frac{1}{L}$.
NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and FHE Bootstrapping
This work proposes NeuJeans, an FHE-based solution for the PI of deep convolutional neural networks (CNNs).
Two-timescale Extragradient for Finding Local Minimax Points
Minimax problems are notoriously challenging to optimize.
HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks
Convolutional neural network (CNN) inference using fully homomorphic encryption (FHE) is a promising private inference (PI) solution due to the capability of FHE that enables offloading the whole computation process to the server while protecting the privacy of sensitive user data.
Hierarchical Text Classification As Sub-Hierarchy Sequence Generation
Consequently, these models are challenging to implement when the model parameters increase for a large-scale hierarchy because the model structure depends on the hierarchy size.
PAM:Point-wise Attention Module for 6D Object Pose Estimation
In GAP, it is designed to pay attention to important information in geometric information, and CAP is designed to pay attention to important information in Channel information.
Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs
We validate our Information Maximizing Hierarchical Conditional Variational AutoEncoder (Info-HCVAE) on several benchmark datasets by evaluating the performance of the QA model (BERT-base) using only the generated QA pairs (QA-based evaluation) or by using both the generated and human-labeled pairs (semi-supervised learning) for training, against state-of-the-art baseline models.
Ranked #1 on
Question Generation
on Natural Questions
Effective Crowdsourcing of Multiple Tasks for Comprehensive Knowledge Extraction
Information extraction from unstructured texts plays a vital role in the field of natural language processing.
