SOTAVerified

Scene Segmentation

Scene segmentation is the task of splitting a scene into its various object components.

Image adapted from Temporally coherent 4D reconstruction of complex dynamic scenes.

Papers

Showing 251275 of 283 papers

TitleStatusHype
Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather ConditionsCode0
Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR DataCode0
CloudAttention: Efficient Multi-Scale Attention Scheme For 3D Point Cloud LearningCode0
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene SegmentationCode0
Relation-Aware Global Attention for Person Re-identificationCode0
ODFNet: Using orientation distribution functions to characterize 3D point cloudsCode0
Scene Parsing via Integrated Classification Model and Variance-Based RegularizationCode0
On Boosting Semantic Street Scene Segmentation with Weak SupervisionCode0
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
One model to use them all: Training a segmentation model with complementary datasetsCode0
The Utility of Decorrelating Colour Spaces in Vector Quantised Variational AutoencodersCode0
Toward Achieving Robust Low-Level and High-Level Scene ParsingCode0
Co-Teaching for Unsupervised Domain Adaptation and ExpansionCode0
A Benchmark for Endoluminal Scene Segmentation of Colonoscopy ImagesCode0
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-LearningCode0
Index NetworkCode0
AttEntropy: On the Generalization Ability of Supervised Semantic Segmentation Transformers to New Objects in New DomainsCode0
Dual Attention Network for Scene SegmentationCode0
Robotic Scene Segmentation with Memory Network for Runtime Surgical Context InferenceCode0
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
End-to-end Learning of Driving Models from Large-scale Video DatasetsCode0
Surgical Scene Segmentation by Transformer With Asymmetric Feature EnhancementCode0
Parsing Natural Scenes and Natural Language with Recursive Neural NetworksCode0
Towards Surgical Context Inference and Translation to GesturesCode0
Path-Invariant Map NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ICMMean IoU50.6Unverified
2Index NetworkMean IoU33.48Unverified
3DeepLab-LargeFOVMean IoU32.08Unverified
4SegNetMean IoU31.84Unverified
5FCNMean IoU27.39Unverified
#ModelMetricClaimedVerifiedStatus
13DMVAverage Accuracy75Unverified
2KPConv3DIoU68.6Unverified
3PointNet++Average Accuracy60.2Unverified
#ModelMetricClaimedVerifiedStatus
1Mask2AnomalyOpen-mIoU59.8Unverified
2LDN121-RPLOpen-mIoU56.3Unverified
3LDN121-DenseHybridOpen-mIoU45.8Unverified
#ModelMetricClaimedVerifiedStatus
1NeighborNetAP71.9Unverified
2TranS4merAP60.78Unverified
#ModelMetricClaimedVerifiedStatus
1UNetFormerCategory mIoU67.8Unverified