28 citations · 46 across the 5 of their papers we have counts for
5 papers
RM-Depth: Unsupervised Learning of Recurrent Monocular Depth in Dynamic Scenes
Tak-Wai Hui
Unsupervised methods have showed promising results on monocular depth estimation. However, the training data must be captured in scenes without moving objects. To push the envelope…
LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation
Tak-Wai Hui, Chen Change Loy
Deep learning approaches have achieved great success in addressing the problem of optical flow estimation. The keys to success lie in the use of cost volume and coarse-to-fine flow…
Inter-Region Affinity Distillation for Road Marking Segmentation
Yuenan Hou, Zheng Ma, Chunxiao Liu +2
We study the problem of distilling knowledge from a large deep teacher network to a much smaller student network for the task of road marking segmentation. In this work, we explore…
Learning to Synthesize Fashion Textures
Wu Shi, Tak-Wai Hui, Ziwei Liu +2
Existing unconditional generative models mainly focus on modeling general objects, such as faces and indoor scenes. Fashion textures, another important type of visual elements arou…
A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization
Tak-Wai Hui, Xiaoou Tang, Chen Change Loy
Over four decades, the majority addresses the problem of optical flow estimation using variational methods. With the advance of machine learning, some recent works have attempted t…