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

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Showing 1351–1400 of 1723 papers

TitleStatusHype
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and ModalitiesCode0
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—0
Factor Graph based 3D Multi-Object Tracking in Point Clouds—0
Global Context Aware Convolutions for 3D Point Cloud Understanding—0
Leveraging Acoustic Images for Effective Self-Supervised Audio Representation LearningCode0
OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets—0
Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery—0
JUMPS: Joints Upsampling Method for Pose Sequences—0
Analogical Image Translation for Fog Generation—0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks—0
MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views—0
From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding—0
Where Does It End? - Reasoning About Hidden Surfaces by Object Intersection ConstraintsCode0
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds—0
Peek-a-Boo: Occlusion Reasoning in Indoor Scenes With Plane Representations—0
FroDO: From Detections to 3D Objects—0
Taskology: Utilizing Task Relations at Scale—0
SUPER: A Novel Lane Detection System—0
FroDO: From Detections to 3D Objects—0
Where Does It End? -- Reasoning About Hidden Surfaces by Object Intersection ConstraintsCode0
Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions—0
MNEW: Multi-domain Neighborhood Embedding and Weighting for Sparse Point Clouds Segmentation—0
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings—0
One-Shot GAN Generated Fake Face Detection—0
High-Accuracy Facial Depth Models derived from 3D Synthetic Data—0
Adversarial Attacks on Monocular Depth Estimation—0
A Robotic 3D Perception System for Operating Room Environment Awareness—0
Neural Mesh Refiner for 6-DoF Pose Estimation—0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset—0
Probabilistic Future Prediction for Video Scene Understanding—0
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation—0
AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted SurgeryCode0
Cross-modal Learning for Multi-modal Video Categorization—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—0
Shallow2Deep: Indoor Scene Modeling by Single Image Understanding—0
3D Gated Recurrent Fusion for Semantic Scene Completion—0
Exploiting Temporal Coherence for Multi-modal Video Categorization—0
PoSeg: Pose-Aware Refinement Network for Human Instance Segmentation—0
Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation—0
Multi-Modal Attention-based Fusion Model for Semantic Segmentation of RGB-Depth Images—0
DADA: Driver Attention Prediction in Driving Accident ScenariosCode0
Inferring Distributions Over Depth from a Single ImageCode0
CNN-based Lidar Point Cloud De-Noising in Adverse WeatherCode0
Scene recognition based on DNN and game theory with its applications in human-robot interaction—0
Deep Learning based Switching Filter for Impulsive Noise Removal in Color ImagesCode0
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object RepresentationsCode0
Language-based Colorization of Scene SketchesCode0
Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image—0
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—0
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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