387 citations · 1.1k across the 38 of their papers we have counts for
30 papers · 1 filter
Joint Spatial-Temporal and Appearance Modeling with Transformer for Multiple Object Tracking
Peng Dai, Yiqiang Feng, Renliang Weng +1
The recent trend in multiple object tracking (MOT) is heading towards leveraging deep learning to boost the tracking performance. In this paper, we propose a novel solution named T…
Searching for Network Width with Bilaterally Coupled Network
Xiu Su, Shan You, Jiyang Xie +4
Searching for a more compact network width recently serves as an effective way of channel pruning for the deployment of convolutional neural networks (CNNs) under hardware constrai…
Weak Augmentation Guided Relational Self-Supervised Learning
Mingkai Zheng, Shan You, Fei Wang +4
Self-supervised Learning (SSL) including the mainstream contrastive learning has achieved great success in learning visual representations without data annotations. However, most m…
GreedyNASv2: Greedier Search with a Greedy Path Filter
Tao Huang, Shan You, Fei Wang +4
Training a good supernet in one-shot NAS methods is difficult since the search space is usually considerably huge (e.g., ). In order to enhance the supernet's evaluation a…
Weakly Supervised Contrastive Learning
Mingkai Zheng, Fei Wang, Shan You +4
Unsupervised visual representation learning has gained much attention from the computer vision community because of the recent achievement of contrastive learning. Most of the exis…
Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
Song Tang, Yan Yang, Zhiyuan Ma +5
In the classic setting of unsupervised domain adaptation (UDA), the labeled source data are available in the training phase. However, in many real-world scenarios, owing to some re…