32 citations · 60 across the 8 of their papers we have counts for
7 papers · 1 filter
High-Quality Entity Segmentation
Lu Qi, Jason Kuen, Weidong Guo +5
Dense image segmentation tasks e.g., semantic, panoptic) are useful for image editing, but existing methods can hardly generalize well in an in-the-wild setting where there are unr…
EfficientNeRF: Efficient Neural Radiance Fields
Tao Hu, Shu Liu, Yilun Chen +2
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes. It takes long per-scene training time and per-image testing…
High Quality Segmentation for Ultra High-resolution Images
Tiancheng Shen, Yuechen Zhang, Lu Qi +5
To segment 4K or 6K ultra high-resolution images needs extra computation consideration in image segmentation. Common strategies, such as down-sampling, patch cropping, and cascade…
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs
Zhengyang Shen, Tiancheng Shen, Zhouchen Lin +1
Spherical signals exist in many applications, e.g., planetary data, LiDAR scans and digitalization of 3D objects, calling for models that can process spherical data effectively. It…
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation
Xia Li, Yibo Yang, Qijie Zhao +3
The convolution operation suffers from a limited receptive filed, while global modeling is fundamental to dense prediction tasks, such as semantic segmentation. In this paper, we a…
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
Zhisheng Zhong, Tiancheng Shen, Yibo Yang +2
Convolutional neural networks (CNNs) have recently achieved great success in single-image super-resolution (SISR). However, these methods tend to produce over-smoothed outputs and…
Convolutional Neural Networks with Alternately Updated Clique
Yibo Yang, Zhisheng Zhong, Tiancheng Shen +1
Improving information flow in deep networks helps to ease the training difficulties and utilize parameters more efficiently. Here we propose a new convolutional neural network arch…