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Found 9 papers, 8 papers with code
PP-MobileSeg: Explore the Fast and Accurate Semantic Segmentation Model on Mobile Devices
To address this issue, we propose PP-MobileSeg, a semantic segmentation model that achieves state-of-the-art performance on mobile devices.
RAIS: Robust and Accurate Interactive Segmentation via Continual Learning
Interactive image segmentation aims at segmenting a target region through a way of human-computer interaction.
EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle
In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks.
U-HRNet: Delving into Improving Semantic Representation of High Resolution Network for Dense Prediction
Therefore, we designed a U-shaped High-Resolution Network (U-HRNet), which adds more stages after the feature map with strongest semantic representation and relaxes the constraint in HRNet that all resolutions need to be calculated parallel for a newly added stage.
PP-Matting: High-Accuracy Natural Image Matting
Also, we propose a semantic context branch (SCB) that adopts a semantic segmentation subtask.
Ranked #4 on
Image Matting
on Distinctions-646
PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model
Real-world applications have high demands for semantic segmentation methods.
Ranked #4 on
Real-Time Semantic Segmentation
on Cityscapes val
PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset
This work is the first to construct a large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K fine-labeled frames and extensions to multi-camera teleconferencing.
EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow
In addition, with the proposed method, we develop an efficient interactive segmentation tool for practical data annotation tasks.
Ranked #2 on
Interactive Segmentation
on PASCAL VOC
(NoC@85 metric)
PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation
The toolkit aims to help both developers and researchers in the whole process of designing segmentation models, training models, optimizing performance and inference speed, and deploying models.
