794 citations · 5.6k across the 185 of their papers we have counts for
20 papers · 2 filters
Revisiting the Transferability of Supervised Pretraining: an MLP Perspective
Yizhou Wang, Shixiang Tang, Feng Zhu +4
The pretrain-finetune paradigm is a classical pipeline in visual learning. Recent progress on unsupervised pretraining methods shows superior transfer performance to their supervis…
Unsupervised Contrastive Learning with Simple Transformation for 3D Point Cloud Data
Jincen Jiang, Xuequan Lu, Wanli Ouyang +1
Though a number of point cloud learning methods have been proposed to handle unordered points, most of them are supervised and require labels for training. By contrast, unsupervise…
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
Yangguang Li, Feng Liang, Lichen Zhao +5
Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferab…
Deep Instance Segmentation with Automotive Radar Detection Points
Jianan Liu, Weiyi Xiong, Liping Bai +4
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the spar…
Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images
Size Wu, Sheng Jin, Wentao Liu +4
This paper studies the task of estimating the 3D human poses of multiple persons from multiple calibrated camera views. Following the top-down paradigm, we decompose the task into…
Towards Balanced Learning for Instance Recognition
Jiangmiao Pang, Kai Chen, Qi Li +5
Instance recognition is rapidly advanced along with the developments of various deep convolutional neural networks. Compared to the architectures of networks, the training process,…