147 citations · 406 across the 16 of their papers we have counts for
6 papers · 1 filter
DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution
Tong He, Chunhua Shen, Anton van den Hengel
Previous top-performing approaches for point cloud instance segmentation involve a bottom-up strategy, which often includes inefficient operations or complex pipelines, such as gro…
FCOS: A simple and strong anchor-free object detector
Zhi Tian, Chunhua Shen, Hao Chen +1
In computer vision, object detection is one of most important tasks, which underpins a few instance-level recognition tasks and many downstream applications. Recently one-stage met…
Improving Semantic Segmentation via Self-Training
Yi Zhu, Zhongyue Zhang, Chongruo Wu +6
Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…
ResNeSt: Split-Attention Networks
Hang Zhang, Chongruo Wu, Zhongyue Zhang +9
It is well known that featuremap attention and multi-path representation are important for visual recognition. In this paper, we present a modularized architecture, which applies t…
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
Yuliang Liu, Hao Chen, Chunhua Shen +3
Scene text detection and recognition has received increasing research attention. Existing methods can be roughly categorized into two groups: character-based and segmentation-based…
Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
Tong He, Dong Gong, Zhi Tian +1
3D point cloud semantic and instance segmentation is crucial and fundamental for 3D scene understanding. Due to the complex structure, point sets are distributed off balance and di…