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 1026–1050 of 1723 papers

TitleStatusHype
Towards A Unified Agent with Foundation Models—0
Human Action Recognition in Still Images Using ConViT—0
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous VehicleCode0
Smart Infrastructure: A Research Junction—0
Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation—0
PSDR-Room: Single Photo to Scene using Differentiable Rendering—0
Object Recognition System on a Tactile Device for Visually Impaired—0
Artifacts Mapping: Multi-Modal Semantic Mapping for Object Detection and 3D Localization—0
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many SynthesisCode0
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties—0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos—0
Semantic-aware Transmission for Robust Point Cloud Classification—0
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation—0
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation—0
DORSal: Diffusion for Object-centric Representations of Scenes et al—0
Neural Projection Mapping Using Reflectance Fields—0
SNeL: A Structured Neuro-Symbolic Language for Entity-Based Multimodal Scene Understanding—0
A Dynamic Feature Interaction Framework for Multi-task Visual Perception—0
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture—0
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses—0
Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing—0
Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes—0
Self-supervised Vision Transformers for 3D Pose Estimation of Novel ObjectsCode0
Dynamic Clustering Transformer Network for Point Cloud Segmentation—0
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph GenerationCode0
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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