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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 283 papers

TitleStatusHype
Attention Discriminant Sampling for Point Clouds—0
AttEntropy: On the Generalization Ability of Supervised Semantic Segmentation Transformers to New Objects in New DomainsCode0
Urban Scene Semantic Segmentation with Low-Cost Coarse Annotation—0
Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation—0
CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars—0
Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene SegmentationCode0
Autonomous Marker-less Rapid Aerial Grasping—0
Improving Pixel-Level Contrastive Learning by Leveraging Exogenous Depth Information—0
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS—0
Transformer-based Flood Scene Segmentation for Developing Countries—0
Point Cloud Recognition with Position-to-Structure Attention Transformers—0
Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation—0
Active Self-Training for Weakly Supervised 3D Scene Semantic Segmentation—0
Introducing Intermediate Domains for Effective Self-Training during Test-TimeCode0
CloudAttention: Efficient Multi-Scale Attention Scheme For 3D Point Cloud LearningCode0
Pseudo-label Guided Cross-video Pixel Contrast for Robotic Surgical Scene Segmentation with Limited Annotations—0
Adversarial Style Augmentation for Domain Generalized Urban-Scene SegmentationCode0
Self-attention on Multi-Shifted Windows for Scene SegmentationCode0
OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification—0
Efficient fine-grained road segmentation using superpixel-based CNN and CRF models—0
ObPose: Leveraging Pose for Object-Centric Scene Inference and Generation in 3D—0
Co-Teaching for Unsupervised Domain Adaptation and ExpansionCode0
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-LearningCode0
Enhancing Local Feature Learning for 3D Point Cloud Processing using Unary-Pairwise Attention—0
CARL-D: A vision benchmark suite and large scale dataset for vehicle detection and scene segmentationCode0
Shift-Memory Network for Temporal Scene Segmentation—0
Amplitude Spectrum Transformation for Open Compound Domain Adaptive Semantic Segmentation—0
Putting 3D Spatially Sparse Networks on a Diet—0
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds—0
Hierarchical Knowledge Distillation for Dialogue Sequence Labeling—0
Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion—0
FBNet: Feature Balance Network for Urban-Scene Segmentation—0
2020 CATARACTS Semantic Segmentation Challenge—0
Unsupervised Contrastive Learning with Simple Transformation for 3D Point Cloud Data—0
Boundary-aware Pre-training for Video Scene Segmentation—0
Predicting Driver Self-Reported Stress by Analyzing the Road Scene—0
PDFNet: Pointwise Dense Flow Network for Urban-Scene SegmentationCode0
A Multimodal Framework for Video Ads Understanding—0
Semantic Scene Segmentation for Robotics Applications—0
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene SegmentationCode0
Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos—0
Potential Convolution: Embedding Point Clouds into Potential Fields—0
Detecting Scenes in Fiction: A new Segmentation Task—0
Fusing RGBD Tracking and Segmentation Tree Sampling for Multi-Hypothesis Volumetric SegmentationCode0
EPRNet: Efficient Pyramid Representation Network for Real-Time Street Scene SegmentationCode0
Arthroscopic Multi-Spectral Scene Segmentation Using Deep Learning—0
Large-Context Conversational Representation Learning: Self-Supervised Learning for Conversational Documents—0
Global-Local Propagation Network for RGB-D Semantic Segmentation—0
Learning Representation in Colour Conversion—0
PARTS: Unsupervised Segmentation With Slots, Attention and Independence Maximization—0
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All datasetsSUN-RGBDScanNetStreetHazardsMovieNetUAVid

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ICMMean IoU50.6—Unverified
2Index NetworkMean IoU33.48—Unverified
3DeepLab-LargeFOVMean IoU32.08—Unverified
4SegNetMean IoU31.84—Unverified
5FCNMean IoU27.39—Unverified
#ModelMetricClaimedVerifiedStatus
13DMVAverage Accuracy75—Unverified
2KPConv3DIoU68.6—Unverified
3PointNet++Average Accuracy60.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Mask2AnomalyOpen-mIoU59.8—Unverified
2LDN121-RPLOpen-mIoU56.3—Unverified
3LDN121-DenseHybridOpen-mIoU45.8—Unverified
#ModelMetricClaimedVerifiedStatus
1NeighborNetAP71.9—Unverified
2TranS4merAP60.78—Unverified
#ModelMetricClaimedVerifiedStatus
1UNetFormerCategory mIoU67.8—Unverified