activity
20162022
most citedNeural Collaborative Subspace Clustering

13 citations · 61 across the 13 of their papers we have counts for

collaborators

19 papers

cs.CV2022

Deformable VisTR: Spatio temporal deformable attention for video instance segmentation

Sudhir Yarram, Jialian Wu, Pan Ji +2

Video instance segmentation (VIS) task requires classifying, segmenting, and tracking object instances over all frames in a video clip. Recently, VisTR has been proposed as end-to-…

cs.CV20212 cited

MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments

Pan Ji, Runze Li, Bir Bhanu +1

Self-supervised depth estimation for indoor environments is more challenging than its outdoor counterpart in at least the following two aspects: (i) the depth range of indoor seque…

cs.CV2021

Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network

Yang Liu, Saeed Anwar, Zhenyue Qin +3

The prevalent convolutional neural network (CNN) based image denoising methods extract features of images to restore the clean ground truth, achieving high denoising accuracy. Howe…

eess.IV202111 cited

Invertible Denoising Network: A Light Solution for Real Noise Removal

Yang Liu, Zhenyue Qin, Saeed Anwar +4

Invertible networks have various benefits for image denoising since they are lightweight, information-lossless, and memory-saving during back-propagation. However, applying inverti…

cs.CV20211 cited

Learning Transferable Kinematic Dictionary for 3D Human Pose and Shape Reconstruction

Ze Ma, Yifan Yao, Pan Ji +1

Estimating 3D human pose and shape from a single image is highly under-constrained. To address this ambiguity, we propose a novel prior, namely kinematic dictionary, which explicit…

cs.CV2020

Set Augmented Triplet Loss for Video Person Re-Identification

Pengfei Fang, Pan Ji, Lars Petersson +1

Modern video person re-identification (re-ID) machines are often trained using a metric learning approach, supervised by a triplet loss. The triplet loss used in video re-ID is usu…