10 citations · 14 across the 4 of their papers we have counts for
7 papers · 1 filter
CFNet: Learning Correlation Functions for One-Stage Panoptic Segmentation
Yifeng Chen, Wenqing Chu, Fangfang Wang +6
Recently, there is growing attention on one-stage panoptic segmentation methods which aim to segment instances and stuff jointly within a fully convolutional pipeline efficiently.…
A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets
Muhammed Muzammul, Xi Li
This survey paper specially analyzed computer vision-based object detection challenges and solutions by different techniques. We mainly highlighted object detection by three differ…
Video Frame Interpolation via Structure-Motion based Iterative Fusion
Xi Li, Meng Cao, Yingying Tang +4
Video Frame Interpolation synthesizes non-existent images between adjacent frames, with the aim of providing a smooth and consistent visual experience. Two approaches for solving t…
Unsupervised segmentation via semantic-apparent feature fusion
Xi Li, Huimin Ma, Hongbing Ma +1
Foreground segmentation is an essential task in the field of image understanding. Under unsupervised conditions, different images and instances always have variable expressions, wh…
Realizing Pixel-Level Semantic Learning in Complex Driving Scenes based on Only One Annotated Pixel per Class
Xi Li, Huimin Ma, Sheng Yi +1
Semantic segmentation tasks based on weakly supervised condition have been put forward to achieve a lightweight labeling process. For simple images that only include a few categori…
WSOD with PSNet and Box Regression
Sheng Yi, Xi Li, Huimin Ma
Weakly supervised object detection(WSOD) task uses only image-level annotations to train object detection task. WSOD does not require time-consuming instance-level annotations, so…