Search Results for author:
Found 7 papers, 2 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.
Neighbor Regularized Bayesian Optimization for Hyperparameter Optimization
Bayesian Optimization (BO) is a common solution to search optimal hyperparameters based on sample observations of a machine learning model.
INTERN: A New Learning Paradigm Towards General Vision
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.
ModuleNet: Knowledge-inherited Neural Architecture Search
Unlike previous search algorithms, and benefiting from inherited knowledge, our method is able to directly search for architectures in the macro space by NSGA-II algorithm without tuning parameters in these \textit{module}s. Experiments show that our strategy can efficiently evaluate the performance of new architecture even without tuning weights in convolutional layers.
