161 citations · 1k across the 45 of their papers we have counts for
6 papers · 1 filter
Memorizing Complementation Network for Few-Shot Class-Incremental Learning
Zhong Ji, Zhishen Hou, Xiyao Liu +2
Few-shot Class-Incremental Learning (FSCIL) aims at learning new concepts continually with only a few samples, which is prone to suffer the catastrophic forgetting and overfitting…
Multi-scale Feature Aggregation for Crowd Counting
Xiaoheng Jiang, Xinyi Wu, Hisham Cholakkal +5
Convolutional Neural Network (CNN) based crowd counting methods have achieved promising results in the past few years. However, the scale variation problem is still a huge challeng…
Reinforced Pedestrian Attribute Recognition with Group Optimization Reward
Zhong Ji, Zhenfei Hu, Yaodong Wang +1
Pedestrian Attribute Recognition (PAR) is a challenging task in intelligent video surveillance. Two key challenges in PAR include complex alignment relations between images and att…
PSTR: End-to-End One-Step Person Search With Transformers
Jiale Cao, Yanwei Pang, Rao Muhammad Anwer +4
We propose a novel one-step transformer-based person search framework, PSTR, that jointly performs person detection and re-identification (re-id) in a single architecture. PSTR com…
Dual-Domain Reconstruction Networks with V-Net and K-Net for fast MRI
Xiaohan Liu, Yanwei Pang, Ruiqi Jin +2
Purpose: To introduce a dual-domain reconstruction network with V-Net and K-Net for accurate MR image reconstruction from undersampled k-space data. Methods: Most state-of-the-art…
Active Phase-Encode Selection for Slice-Specific Fast MR Scanning Using a Transformer-Based Deep Reinforcement Learning Framework
Yiming Liu, Yanwei Pang, Ruiqi Jin +1
Purpose: Long scan time in phase encoding for forming complete K-space matrices is a critical drawback of MRI, making patients uncomfortable and wasting important time for diagnosi…