858 citations · 1.4k across the 7 of their papers we have counts for
4 papers · 1 filter
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
Zifeng Wu, Chunhua Shen, Anton van den Hengel
The trend towards increasingly deep neural networks has been driven by a general observation that increasing depth increases the performance of a network. Recently, however, eviden…
Bridging Category-level and Instance-level Semantic Image Segmentation
Zifeng Wu, Chunhua Shen, Anton van den Hengel
We propose an approach to instance-level image segmentation that is built on top of category-level segmentation. Specifically, for each pixel in a semantic category mask, its corre…
Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks
Yuanzhouhan Cao, Zifeng Wu, Chunhua Shen
Depth estimation from single monocular images is a key component of scene understanding and has benefited largely from deep convolutional neural networks (CNN) recently. In this ar…
High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks
Zifeng Wu, Chunhua Shen, Anton van den Hengel
We propose a method for high-performance semantic image segmentation (or semantic pixel labelling) based on very deep residual networks, which achieves the state-of-the-art perform…