activity
20172023
most citedCost-Effective Active Learning for Deep Image Classification

676 citations · 725 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20236 cited

Boosting Human-Object Interaction Detection with Text-to-Image Diffusion Model

Jie Yang, Bingliang Li, Fengyu Yang +3

This paper investigates the problem of the current HOI detection methods and introduces DiffHOI, a novel HOI detection scheme grounded on a pre-trained text-image diffusion model,…

cs.LG20238 cited

Hierarchical Weight Averaging for Deep Neural Networks

Xiaozhe Gu, Zixun Zhang, Yuncheng Jiang +4

Despite the simplicity, stochastic gradient descent (SGD)-like algorithms are successful in training deep neural networks (DNNs). Among various attempts to improve SGD, weight aver…

cs.CV202310 cited

Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation

Ye Zhu, Jie Yang, Si-Qi Liu +1

Semi-supervised medical image segmentation has attracted much attention in recent years because of the high cost of medical image annotations. In this paper, we propose a novel Inh…

cs.CV20231 cited

Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domains

Jie Yang, Chaoqun Wang, Zhen Li +2

This paper presents Scalable Semantic Transfer (SST), a novel training paradigm, to explore how to leverage the mutual benefits of the data from different label domains (i.e. vario…

cs.CV202217 cited

2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds

Xu Yan, Jiantao Gao, Chaoda Zheng +4

As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-mod…

cs.CV20217 cited

MetaCloth: Learning Unseen Tasks of Dense Fashion Landmark Detection from a Few Samples

Yuying Ge, Ruimao Zhang, Ping Luo

Recent advanced methods for fashion landmark detection are mainly driven by training convolutional neural networks on large-scale fashion datasets, which has a large number of anno…