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Found 11 papers, 3 papers with code
Mask Hierarchical Features For Self-Supervised Learning
We mask part of patches in the representation space and then utilize sparse visible patches to reconstruct high semantic image representation.
Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline
Our Fast-BEV consists of five parts, We novelly propose (1) a lightweight deployment-friendly view transformation which fast transfers 2D image feature to 3D voxel space, (2) an multi-scale image encoder which leverages multi-scale information for better performance, (3) an efficient BEV encoder which is particularly designed to speed up on-vehicle inference.
Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception
Recently, the pure camera-based Bird's-Eye-View (BEV) perception removes expensive Lidar sensors, making it a feasible solution for economical autonomous driving.
Parallel Reasoning Network for Human-Object Interaction Detection
Human-Object Interaction (HOI) detection aims to learn how human interacts with surrounding objects.
One Sample Diffusion Model in Projection Domain for Low-Dose CT Imaging
Therefore, we propose a fully unsupervised one sample diffusion model (OSDM)in projection domain for low-dose CT reconstruction.
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
A detailed description of all models developed in the challenge is provided in this paper.
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
Herein, we present GraphTheta, the first distributed and scalable graph learning system built upon vertex-centric distributed graph processing with neural network operators implemented as user-defined functions.
Global Strong Solutions to the Compressible Magnetohydrodynamic Equations with Slip Boundary Conditions in 3D Bounded Domains
We deal with the barotropic compressible magnetohydrodynamic equations in three-dimensional (3D) bounded domain with slip boundary condition and vacuum.
Analysis of PDEs
Computational prediction of RNA tertiary structures using machine learning methods
RNAs play crucial and versatile roles in biological processes.
Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by Random Circuit Perturbation
These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN.
FoxNet: A Multi-face Alignment Method
Multi-face alignment aims to identify geometry structures of multiple faces in an image, and its performance is essential for the many practical tasks, such as face recognition, face tracking, and face animation.
