SOTAVerified

Scene Parsing

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

Papers

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Showing 51–100 of 199 papers

TitleStatusHype
Dynamic Multi-Scale Filters for Semantic SegmentationCode0
Improving Panoptic Segmentation for Nighttime or Low-Illumination Urban Driving ScenesCode0
Applying Unsupervised Semantic Segmentation to High-Resolution UAV Imagery for Enhanced Road Scene ParsingCode0
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed dataCode0
SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV ApplicationsCode0
Boosting Real-Time Driving Scene Parsing with Shared SemanticsCode0
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene ParsingCode0
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse ConvolutionsCode0
HAPNet: Toward Superior RGB-Thermal Scene Parsing via Hybrid, Asymmetric, and Progressive Heterogeneous Feature FusionCode0
What's There in the DarkCode0
SalientDSO: Bringing Attention to Direct Sparse OdometryCode0
Convolutional Neural Network Language ModelsCode0
PSANet: Point-wise Spatial Attention Network for Scene ParsingCode0
Structured Knowledge Distillation for Dense PredictionCode0
Structured Knowledge Distillation for Semantic SegmentationCode0
Unlocking the Full Potential of Small Data with Diverse SupervisionCode0
Scene Parsing via Integrated Classification Model and Variance-Based RegularizationCode0
Scene Parsing with Global Context EmbeddingCode0
A Dilated Residual Hierarchically Fashioned Segmentation Framework for Extracting Gleason Tissues and Grading Prostate Cancer from Whole Slide ImagesCode0
LF Tracy: A Unified Single-Pipeline Approach for Salient Object Detection in Light Field CamerasCode0
Synscapes: A Photorealistic Synthetic Dataset for Street Scene ParsingCode0
Complete 3D Scene Parsing from an RGBD ImageCode0
Auto-Retoucher(ART) - A framework for Background Replacement and Image EditingCode0
Adaptive Pyramid Context Network for Semantic SegmentationCode0
Toward Achieving Robust Low-Level and High-Level Scene ParsingCode0
PIG: Prompt Images Guidance for Night-Time Scene ParsingCode0
Oceanic Eddy Identification Using an AI Scheme—0
OLAF: A Plug-and-Play Framework for Enhanced Multi-object Multi-part Scene Parsing—0
Open Vocabulary Scene Parsing—0
ORDNet: Capturing Omni-Range Dependencies for Scene Parsing—0
PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing—0
Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired—0
Predicting Scene Parsing and Motion Dynamics in the Future—0
Radar Spectra-Language Model for Automotive Scene Parsing—0
Real-Time Panoptic Segmentation from Dense Detections—0
Recurrent Convolutional Neural Networks for Scene Parsing—0
Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing—0
Re:PolyWorld - A Graph Neural Network for Polygonal Scene Parsing—0
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization—0
RoadFormer+: Delivering RGB-X Scene Parsing through Scale-Aware Information Decoupling and Advanced Heterogeneous Feature Fusion—0
RoadFormer: Duplex Transformer for RGB-Normal Semantic Road Scene Parsing—0
SAI3D: Segment Any Instance in 3D Scenes—0
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering—0
Scale-Adaptive Convolutions for Scene Parsing—0
Scene Parsing by Integrating Function, Geometry and Appearance Models—0
Scene Parsing Through ADE20K Dataset—0
Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection—0
Scene Parsing with Integration of Parametric and Non-parametric Models—0
Scene Parsing with Object Instances and Occlusion Ordering—0
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction—0
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All datasetsPGDP5KCityscapes test

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PGDPNetTotal Accuracy84.7—Unverified
2Inter-GPSTotal Accuracy27.3—Unverified
#ModelMetricClaimedVerifiedStatus
1VCD No CoarsemIoU82.3—Unverified