Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline

1 code implementation • 29 Jan 2023 • Yangguang Li, Bin Huang, Zeren Chen, Yufeng Cui, Feng Liang, Mingzhu Shen, Fenggang Liu, Enze Xie, Lu Sheng, Wanli Ouyang, Jing Shao

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.

Data Augmentation

Multi-Modal Gait Recognition via Effective Spatial-Temporal Feature Fusion

no code implementations • CVPR 2023 • Yufeng Cui, Yimei Kang

The SFM performs fine-grained body parts spatial fusion and guides the alignment of each part of the silhouette and each joint of the skeleton through the attention mechanism.

Gait Recognition

Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision

1 code implementation • 11 Mar 2022 • Yufeng Cui, Lichen Zhao, Feng Liang, Yangguang Li, Jing Shao

This is because researchers do not choose consistent training recipes and even use different data, hampering the fair comparison between different methods.

Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

2 code implementations • ICLR 2022 • Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang, Jing Shao, Fengwei Yu, Junjie Yan

Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks.

Zero-Shot Learning