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 226250 of 283 papers

TitleStatusHype
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene SegmentationCode0
Example-Guided Style Consistent Image Synthesis from Semantic LabelingCode0
Loci-Segmented: Improving Scene Segmentation LearningCode0
Adversarial Style Augmentation for Domain Generalized Urban-Scene SegmentationCode0
DepthComp: real-time depth image completion based on prior semantic scene segmentationCode0
Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene SegmentationCode0
The RGB-D Triathlon: Towards Agile Visual Toolboxes for RobotsCode0
Fast and Efficient: Mask Neural Fields for 3D Scene SegmentationCode0
Fast Scene Understanding for Autonomous DrivingCode0
Point-Voxel CNN for Efficient 3D Deep LearningCode0
MCDS-VSS: Moving Camera Dynamic Scene Video Semantic Segmentation by Filtering with Self-Supervised Geometry and MotionCode0
Boundary-Aware Feature Propagation for Scene SegmentationCode0
Semantic Stereo for Incidental Satellite ImagesCode0
Self-attention on Multi-Shifted Windows for Scene SegmentationCode0
Seamless Scene SegmentationCode0
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance SegmentationCode0
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene UnderstandingCode0
PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic SegmentationCode0
Fully Convolutional Networks for Semantic SegmentationCode0
Fusing RGBD Tracking and Segmentation Tree Sampling for Multi-Hypothesis Volumetric SegmentationCode0
Handling new target classes in semantic segmentation with domain adaptationCode0
CARL-D: A vision benchmark suite and large scale dataset for vehicle detection and scene segmentationCode0
Efficient Yet Deep Convolutional Neural Networks for Semantic SegmentationCode0
PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel FramesCode0
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene SegmentationCode0
Show:102550
← PrevPage 10 of 12Next →

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