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 326–350 of 1723 papers

TitleStatusHype
From General to Specific: Informative Scene Graph Generation via Balance AdjustmentCode1
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving ScenesCode1
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene UnderstandingCode1
Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic SegmentationCode1
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic DataCode1
All-Day Multi-Camera Multi-Target TrackingCode1
Learning Triadic Belief Dynamics in Nonverbal Communication from VideosCode1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene UnderstandingCode1
DAF-Net: A Dual-Branch Feature Decomposition Fusion Network with Domain Adaptive for Infrared and Visible Image FusionCode1
Light Field Networks: Neural Scene Representations with Single-Evaluation RenderingCode1
LinkNet: Exploiting Encoder Representations for Efficient Semantic SegmentationCode1
LLaVA-SpaceSGG: Visual Instruct Tuning for Open-vocabulary Scene Graph Generation with Enhanced Spatial RelationsCode1
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household RoboticsCode1
Few-Shot Object Detection and Viewpoint Estimation for Objects in the WildCode1
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous DrivingCode1
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion FramesCode1
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous DrivingCode1
Masked Scene Modeling: Narrowing the Gap Between Supervised and Self-Supervised Learning in 3D Scene UnderstandingCode1
MassMIND: Massachusetts Maritime INfrared DatasetCode1
AVSegFormer: Audio-Visual Segmentation with TransformerCode1
MGNet: Monocular Geometric Scene Understanding for Autonomous DrivingCode1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed ImagesCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
A Versatile and Efficient Reinforcement Learning Framework for Autonomous DrivingCode1
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud SegmentationCode1
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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