Scene Parsing
75 papers with code • 2 benchmarks • 4 datasets
Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description
Benchmarks
These leaderboards are used to track progress in Scene Parsing
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Libraries
Use these libraries to find Scene Parsing models and implementations
Cityscapes
Stanford Background
PGDP5K
UNDD
Subtasks
Most implemented papers
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
A key algorithm for understanding the world is material segmentation, which assigns a label (metal, glass, etc.)
OneFormer: One Transformer to Rule Universal Image Segmentation
SHI-Labs/OneFormer
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CVPR 2023
However, such panoptic architectures do not truly unify image segmentation because they need to be trained individually on the semantic, instance, or panoptic segmentation to achieve the best performance.
Recurrent Scene Parsing with Perspective Understanding in the Loop
We propose a depth-aware gating module that adaptively selects the pooling field size in a convolutional network architecture according to the object scale (inversely proportional to the depth) so that small details are preserved for distant objects while larger receptive fields are used for those nearby.
Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF
The proposed joint model also employs a guidance CRF to further enhance the segmentation performance.
Dual-Glance Model for Deciphering Social Relationships
Since the beginning of early civilizations, social relationships derived from each individual fundamentally form the basis of social structure in our daily life.
Scene Parsing with Global Context Embedding
We present a scene parsing method that utilizes global context information based on both the parametric and non- parametric models.
Complete 3D Scene Parsing from an RGBD Image
In this paper, we aim to interpret indoor scenes from one RGBD image.
SalientDSO: Bringing Attention to Direct Sparse Odometry
We merge the successes of these two communities and present a way to incorporate semantic information in the form of visual saliency to Direct Sparse Odometry - a highly successful direct sparse VO algorithm.
DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map
pengwangucla/DeLS-3D
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CVPR 2018
The uniqueness of our design is a sensor fusion scheme which integrates camera videos, motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robustness and efficiency of the system.
