activity
20182020
most citedBeyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

19 citations · 26 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202019 cited

Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

Cheng Yan, Guansong Pang, Xiao Bai +2

Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras. Capturing the fine-grained appearance differences is often the key…

cs.CV2020

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

Zewen Li, Wenjie Yang, Shouheng Peng +1

Convolutional Neural Network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limit…

eess.AS20207 cited

Deep Residual-Dense Lattice Network for Speech Enhancement

Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao +3

Convolutional neural networks (CNNs) with residual links (ResNets) and causal dilated convolutional units have been the network of choice for deep learning approaches to speech enh…

cs.CV2019

A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks

Dong Wang, Lei Zhou, Xiao Bai +1

Acceleration of convolutional neural network has received increasing attention during the past several years. Among various acceleration techniques, filter pruning has its inherent…

cs.CV2018

Material Based Object Tracking in Hyperspectral Videos: Benchmark and Algorithms

Fengchao Xiong, Jun Zhou, Yuntao Qian

Traditional color images only depict color intensities in red, green and blue channels, often making object trackers fail in challenging scenarios, e.g., background clutter and rap…