activity
20182026
most citedDETR for Crowd Pedestrian Detection

38 citations · 116 across the 11 of their papers we have counts for

collaborators
Showing 2020Show all

8 papers · 1 filter

cs.CV2020

Inception Convolution with Efficient Dilation Search

Jie Liu, Chuming Li, Feng Liang +5

As a variant of standard convolution, a dilated convolution can control effective receptive fields and handle large scale variance of objects without introducing additional computa…

cs.CV202038 cited

DETR for Crowd Pedestrian Detection

Matthieu Lin, Chuming Li, Xingyuan Bu +5

Pedestrian detection in crowd scenes poses a challenging problem due to the heuristic defined mapping from anchors to pedestrians and the conflict between NMS and highly overlapped…

cs.CV20207 cited

PV-NAS: Practical Neural Architecture Search for Video Recognition

Zihao Wang, Chen Lin, Lu Sheng +2

Recently, deep learning has been utilized to solve video recognition problem due to its prominent representation ability. Deep neural networks for video tasks is highly customized…

cs.CV2020

Evolving Search Space for Neural Architecture Search

Yuanzheng Ci, Chen Lin, Ming Sun +3

The automation of neural architecture design has been a coveted alternative to human experts. Recent works have small search space, which is easier to optimize but has a limited up…

cs.LG2020

Improving Auto-Augment via Augmentation-Wise Weight Sharing

Keyu Tian, Chen Lin, Ming Sun +3

The recent progress on automatically searching augmentation policies has boosted the performance substantially for various tasks. A key component of automatic augmentation search i…

cs.LG2020

Adaptive Gradient Method with Resilience and Momentum

Jie Liu, Chen Lin, Chuming Li +4

Several variants of stochastic gradient descent (SGD) have been proposed to improve the learning effectiveness and efficiency when training deep neural networks, among which some r…