activity
20192022
most citedPCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval

22 citations · 59 across the 8 of their papers we have counts for

collaborators

12 papers

cs.CV20224 cited

NeuralRoom: Geometry-Constrained Neural Implicit Surfaces for Indoor Scene Reconstruction

Yusen Wang, Zongcheng Li, Yu Jiang +4

We present a novel neural surface reconstruction method called NeuralRoom for reconstructing room-sized indoor scenes directly from a set of 2D images. Recently, implicit neural re…

cs.CV20223 cited

DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation

Tuo Cao, Fei Luo, Yanping Fu +3

Monocular 6D pose estimation is a fundamental task in computer vision. Existing works often adopt a two-stage pipeline by establishing correspondences and utilizing a RANSAC algori…

cs.CV20211 cited

Luminance Attentive Networks for HDR Image and Panorama Reconstruction

Hanning Yu, Wentao Liu, Chengjiang Long +3

It is very challenging to reconstruct a high dynamic range (HDR) from a low dynamic range (LDR) image as an ill-posed problem. This paper proposes a luminance attentive network nam…

cs.CV20213 cited

CANet: A Context-Aware Network for Shadow Removal

Zipei Chen, Chengjiang Long, Ling Zhang +1

In this paper, we propose a novel two-stage context-aware network named CANet for shadow removal, in which the contextual information from non-shadow regions is transferred to shad…

cs.CV20214 cited

Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning

Xinzhi Dong, Chengjiang Long, Wenju Xu +1

Existing image captioning methods just focus on understanding the relationship between objects or instances in a single image, without exploring the contextual correlation existed…

cs.CV2021

CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-to-Image Generation

Tao Hu, Chengjiang Long, Chunxia Xiao

Generating photo-realistic images from a text description is a challenging problem in computer vision. Previous works have shown promising performance to generate synthetic images…