Search Results for author:
Found 3 papers, 2 papers with code
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
We first investigate self-supervised learning (SSL) methods with Vision Transformer (ViT) pretrained on unlabelled person images (the LUPerson dataset), and empirically find it significantly surpasses ImageNet supervised pre-training models on ReID tasks.
Ranked #1 on
Unsupervised Person Re-Identification
on Market-1501
(using extra training data)
Goal-Guided Transformer-Enabled Reinforcement Learning for Efficient Autonomous Navigation
Despite some successful applications of goal-driven navigation, existing deep reinforcement learning (DRL)-based approaches notoriously suffers from poor data efficiency issue.
A Marker-free Head Tracker Using Vision-based Head Pose Estimation with Adaptive Kalman Filter
To handle the error of the head pose estimation model, this paper proposes an adaptive Kalman Filter.
