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 76100 of 283 papers

TitleStatusHype
ROAD-Waymo: Action Awareness at Scale for Autonomous DrivingCode1
Efficient Movie Scene Detection using State-Space TransformersCode1
Boundary-aware Self-supervised Learning for Video Scene SegmentationCode1
Self-positioning Point-based Transformer for Point Cloud UnderstandingCode1
Learning and Reasoning with the Graph Structure Representation in Robotic SurgeryCode1
PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic SegmentationCode0
Point-Voxel CNN for Efficient 3D Deep LearningCode0
Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather ConditionsCode0
Parsing Natural Scenes and Natural Language with Recursive Neural NetworksCode0
Path-Invariant Map NetworksCode0
Co-Teaching for Unsupervised Domain Adaptation and ExpansionCode0
AttEntropy: On the Generalization Ability of Supervised Semantic Segmentation Transformers to New Objects in New DomainsCode0
PDFNet: Pointwise Dense Flow Network for Urban-Scene SegmentationCode0
Relation-Aware Global Attention for Person Re-identificationCode0
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene SegmentationCode0
PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel FramesCode0
Adversarial Style Augmentation for Domain Generalized Urban-Scene SegmentationCode0
On Boosting Semantic Street Scene Segmentation with Weak SupervisionCode0
One model to use them all: Training a segmentation model with complementary datasetsCode0
Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene SegmentationCode0
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene UnderstandingCode0
A Benchmark for Endoluminal Scene Segmentation of Colonoscopy ImagesCode0
ODFNet: Using orientation distribution functions to characterize 3D point cloudsCode0
Learning Rich Features from RGB-D Images for Object Detection and SegmentationCode0
CloudAttention: Efficient Multi-Scale Attention Scheme For 3D Point Cloud LearningCode0
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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