activity
20182021
most citedLearn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting

79 citations · 166 across the 10 of their papers we have counts for

collaborators

23 papers

cs.CV20211 cited

Towards Adversarially Robust and Domain Generalizable Stereo Matching by Rethinking DNN Feature Backbones

Kelvin Cheng, Christopher Healey, Tianfu Wu

Stereo matching has recently witnessed remarkable progress using Deep Neural Networks (DNNs). But, how robust are they? Although it has been well-known that DNNs often suffer from…

cs.CV2021

PlaneTR: Structure-Guided Transformers for 3D Plane Recovery

Bin Tan, Nan Xue, Song Bai +2

This paper presents a neural network built upon Transformers, namely PlaneTR, to simultaneously detect and reconstruct planes from a single image. Different from previous methods,…

cs.CV20212 cited

Deep Consensus Learning

Wei Sun, Tianfu Wu

Both generative learning and discriminative learning have recently witnessed remarkable progress using Deep Neural Networks (DNNs). For structured input synthesis and structured ou…

cs.LG2020

Local Clustering with Mean Teacher for Semi-supervised Learning

Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra +2

The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable performance on several semi-supervised benchmark datasets. MT maintains a teacher model's weights as the ex…

cs.CV20201 cited

Holistically-Attracted Wireframe Parsing

Nan Xue, Tianfu Wu, Song Bai +4

This paper presents a fast and parsimonious parsing method to accurately and robustly detect a vectorized wireframe in an input image with a single forward pass. The proposed metho…

cs.CV2020

Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis

Wei Sun, Tianfu Wu

With the remarkable recent progress on learning deep generative models, it becomes increasingly interesting to develop models for controllable image synthesis from reconfigurable i…