SOTAVerified

Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1401–1450 of 1723 papers

TitleStatusHype
Addressing the Sim2Real Gap in Robotic 3D Object Classification—0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
GANspection—0
Deep Contextual Attention for Human-Object Interaction Detection—0
Deep Semantic Segmentation of Natural and Medical Images: A Review—0
Semantic Understanding of Foggy Scenes with Purely Synthetic DataCode0
Using Image Priors to Improve Scene Understanding—0
Real-Time Semantic Stereo Matching—0
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency DetectionCode0
Multi-view PointNet for 3D Scene Understanding—0
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving—0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
On the Pareto Efficiency of Quantized CNN—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
Simultaneous Segmentation and Recognition: Towards more accurate Ego Gesture Recognition—0
Pose-aware Multi-level Feature Network for Human Object Interaction DetectionCode0
Multi-Task Learning for Automotive Foggy Scene Understanding via Domain Adaptation to an Illumination-Invariant Representation—0
Visuomotor Understanding for Representation Learning of Driving Scenes—0
Semantic Foreground Inpainting from Weak SupervisionCode0
DublinCity: Annotated LiDAR Point Cloud and its Applications—0
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense—0
Texture Underfitting for Domain Adaptation—0
Rotation Invariant Convolutions for 3D Point Clouds Deep LearningCode0
RIO: 3D Object Instance Re-Localization in Changing Indoor EnvironmentsCode0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes—0
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and ClassificationCode0
Object as Distribution—0
Improving Social Awareness Through DANTE: A Deep Affinity Network for Clustering Conversational InteractantsCode0
SDNet: Semantically Guided Depth Estimation Network—0
U4D: Unsupervised 4D Dynamic Scene Understanding—0
Temporally Consistent Horizon LinesCode0
Structure-Aware Residual Pyramid Network for Monocular Depth EstimationCode0
Preferences Prediction using a Gallery of Mobile Device based on Scene Recognition and Object DetectionCode0
CaDIS: Cataract Dataset for Image Segmentation—0
Loss Switching Fusion with Similarity Search for Video ClassificationCode0
Active Scene Understanding via Online Semantic Reconstruction—0
Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes—0
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding—0
RailSem19: A Dataset for Semantic Rail Scene Understanding—0
A New Ratio Image Based CNN Algorithm For SAR Despeckling—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Panoptic Edge Detection—0
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera—0
Towards Scene Understanding: Unsupervised Monocular Depth Estimation With Semantic-Aware Representation—0
Distraction-Aware Shadow Detection—0
Not Using the Car to See the Sidewalk -- Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Learning to Detect Human-Object Interactions With Knowledge—0
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from VideoCode0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified