Portrait Segmentation
6 papers with code • 1 benchmarks • 3 datasets
P3M-10k
PP-HumanSeg14K
EasyPortrait
Most implemented papers
SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder
clovaai/c3_sinet
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To solve the first problem, we introduce the new extremely lightweight portrait segmentation model SINet, containing an information blocking decoder and spatial squeeze modules.
ExtremeC3Net: Extreme Lightweight Portrait Segmentation Networks using Advanced C3-modules
In our qualitative and quantitative analysis on the EG1800 dataset, we show that our method outperforms various existing lightweight segmentation models.
Boundary-Aware Network for Fast and High-Accuracy Portrait Segmentation
lewisluk/BoundaryAwareNetwork
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Compared with other semantic segmentation tasks, portrait segmentation requires both higher precision and faster inference speed.
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.
Portrait Segmentation Using Deep Learning
A portrait is a painting, drawing, photograph, or engraving of a person, especially one depicting only the face or head and shoulders.
EasyPortrait -- Face Parsing and Portrait Segmentation Dataset
Limited variability in existing portrait segmentation and face parsing datasets, including head poses, ethnicity, scenes, and occlusions specific to video conferencing, motivated us to create a new dataset, EasyPortrait, for these tasks simultaneously.
